diff --git a/.envrc b/.envrc
new file mode 100644
index 000000000..bb13dae3a
--- /dev/null
+++ b/.envrc
@@ -0,0 +1 @@
+use devenv
diff --git a/.gitignore b/.gitignore
index 636d655bf..aec7db50f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -81,7 +81,7 @@ profile_default/
 ipython_config.py
 
 # pyenv
-.python-version
+# .python-version — tracked as single source of truth for Python version
 
 # pipenv
 Pipfile.lock
@@ -178,6 +178,11 @@ CLAUDE.local.md
 # Claude Code personal settings
 .claude/settings.local.json
 
+# devenv (local overrides only - devenv.nix/yaml/.envrc are committed)
+.devenv/
+devenv.lock
+devenv.local.yaml
+
 # Standalone mode files
 .pal_venv/
 .docker_cleaned
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 582f913d9..53347278a 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -28,9 +28,9 @@ exclude: |
     \.git/|
     \.venv/|
     venv/|
-    \.pal_venv/|
     __pycache__/|
     \.pytest_cache/|
+    \.devenv/|
     logs/|
     dist/|
     build/|
diff --git a/.python-version b/.python-version
new file mode 100644
index 000000000..6324d401a
--- /dev/null
+++ b/.python-version
@@ -0,0 +1 @@
+3.14
diff --git a/clink/agents/base.py b/clink/agents/base.py
index 523b68887..c6afe04fa 100644
--- a/clink/agents/base.py
+++ b/clink/agents/base.py
@@ -125,7 +125,7 @@ async def run(
                 process.communicate(prompt.encode("utf-8")),
                 timeout=self.client.timeout_seconds,
             )
-        except asyncio.TimeoutError as exc:
+        except TimeoutError as exc:
             process.kill()
             await process.communicate()
             raise CLIAgentError(
diff --git a/code_quality_checks.sh b/code_quality_checks.sh
index d58dcbfe8..23762bfd1 100755
--- a/code_quality_checks.sh
+++ b/code_quality_checks.sh
@@ -3,101 +3,58 @@
 # PAL MCP Server - Code Quality Checks
 # This script runs all required linting and testing checks before committing changes.
 # ALL checks must pass 100% for CI/CD to succeed.
+#
+# Requires: devenv shell (uv, ruff, black, isort, pytest available via `uv run`)
 
 set -e  # Exit on any error
 
-echo "🔍 Running Code Quality Checks for PAL MCP Server"
+echo "Running Code Quality Checks for PAL MCP Server"
 echo "================================================="
 
-# Determine Python command
-if [[ -f ".pal_venv/bin/python" ]]; then
-    PYTHON_CMD=".pal_venv/bin/python"
-    PIP_CMD=".pal_venv/bin/pip"
-    echo "✅ Using venv"
-elif [[ -n "$VIRTUAL_ENV" ]]; then
-    PYTHON_CMD="python"
-    PIP_CMD="pip"
-    echo "✅ Using activated virtual environment: $VIRTUAL_ENV"
-else
-    echo "❌ No virtual environment found!"
-    echo "Please run: ./run-server.sh first to set up the environment"
+# Ensure uv is available
+if ! command -v uv &> /dev/null; then
+    echo "Error: uv not found. Activate devenv first (cd into repo with direnv, or run devenv shell)."
     exit 1
 fi
-echo ""
-
-# Check and install dev dependencies if needed
-echo "🔍 Checking development dependencies..."
-DEV_DEPS_NEEDED=false
 
-# Check each dev dependency
-for tool in ruff black isort pytest; do
-    # Check if tool exists in venv or in PATH
-    if [[ -f ".pal_venv/bin/$tool" ]] || command -v $tool &> /dev/null; then
-        continue
-    else
-        DEV_DEPS_NEEDED=true
-        break
-    fi
-done
-
-if [ "$DEV_DEPS_NEEDED" = true ]; then
-    echo "📦 Installing development dependencies..."
-    $PIP_CMD install -q -r requirements-dev.txt
-    echo "✅ Development dependencies installed"
-else
-    echo "✅ Development dependencies already installed"
-fi
-
-# Set tool paths
-if [[ -f ".pal_venv/bin/ruff" ]]; then
-    RUFF=".pal_venv/bin/ruff"
-    BLACK=".pal_venv/bin/black"
-    ISORT=".pal_venv/bin/isort"
-    PYTEST=".pal_venv/bin/pytest"
-else
-    RUFF="ruff"
-    BLACK="black"
-    ISORT="isort"
-    PYTEST="pytest"
-fi
+# Sync deps if needed
+echo "Syncing dependencies..."
+uv sync --quiet
 echo ""
 
 # Step 1: Linting and Formatting
-echo "📋 Step 1: Running Linting and Formatting Checks"
+echo "Step 1: Running Linting and Formatting Checks"
 echo "--------------------------------------------------"
 
-echo "🔧 Running ruff linting with auto-fix..."
-$RUFF check --fix --exclude test_simulation_files --exclude .pal_venv
+echo "Running ruff linting with auto-fix..."
+ruff check --fix --exclude test_simulation_files --exclude .devenv
 
-echo "🎨 Running black code formatting..."
-$BLACK . --exclude="test_simulation_files/" --exclude=".pal_venv/"
+echo "Running black code formatting..."
+black . --exclude="test_simulation_files/|\.devenv/"
 
-echo "📦 Running import sorting with isort..."
-$ISORT . --skip-glob=".pal_venv/*" --skip-glob="test_simulation_files/*"
+echo "Running import sorting with isort..."
+isort . --skip-glob="test_simulation_files/*" --skip-glob=".devenv/*"
 
-echo "✅ Verifying all linting passes..."
-$RUFF check --exclude test_simulation_files --exclude .pal_venv
+echo "Verifying all linting passes..."
+ruff check --exclude test_simulation_files --exclude .devenv
 
-echo "✅ Step 1 Complete: All linting and formatting checks passed!"
+echo "Step 1 Complete: All linting and formatting checks passed!"
 echo ""
 
 # Step 2: Unit Tests
-echo "🧪 Step 2: Running Complete Unit Test Suite"
+echo "Step 2: Running Complete Unit Test Suite"
 echo "---------------------------------------------"
 
-echo "🏃 Running unit tests (excluding integration tests)..."
-$PYTHON_CMD -m pytest tests/ -v -x -m "not integration"
+echo "Running unit tests (excluding integration tests)..."
+pytest tests/ -v -x -m "not integration"
 
-echo "✅ Step 2 Complete: All unit tests passed!"
+echo "Step 2 Complete: All unit tests passed!"
 echo ""
 
 # Step 3: Final Summary
-echo "🎉 All Code Quality Checks Passed!"
+echo "All Code Quality Checks Passed!"
 echo "=================================="
-echo "✅ Linting (ruff): PASSED"
-echo "✅ Formatting (black): PASSED" 
-echo "✅ Import sorting (isort): PASSED"
-echo "✅ Unit tests: PASSED"
-echo ""
-echo "🚀 Your code is ready for commit and GitHub Actions!"
-echo "💡 Remember to add simulator tests if you modified tools"
\ No newline at end of file
+echo "Linting (ruff): PASSED"
+echo "Formatting (black): PASSED"
+echo "Import sorting (isort): PASSED"
+echo "Unit tests: PASSED"
diff --git a/conf/gemini_models.json b/conf/gemini_models.json
index 05372e301..02535dd3c 100644
--- a/conf/gemini_models.json
+++ b/conf/gemini_models.json
@@ -26,15 +26,16 @@
   },
   "models": [
     {
-      "model_name": "gemini-3-pro-preview",
-      "friendly_name": "Gemini Pro 3.0 Preview",
+      "model_name": "gemini-3.1-pro-preview",
+      "friendly_name": "Gemini Pro 3.1 Preview",
       "aliases": [
         "pro",
         "gemini3",
-        "gemini-pro"
+        "gemini-pro",
+        "gemini3.1"
       ],
       "intelligence_score": 18,
-      "description": "Deep reasoning + thinking mode (1M context) - Complex problems, architecture, deep analysis",
+      "description": "Gemini 3.1 Pro (1M context, 65K output) - Flagship reasoning with thinking_level support, vision, computer use",
       "context_window": 1048576,
       "max_output_tokens": 65536,
       "max_thinking_tokens": 32768,
@@ -54,8 +55,8 @@
       "aliases": [
         "gemini-pro-2.5"
       ],
-      "intelligence_score": 18,
-      "description": "Older Model. 1M context - Complex problems, architecture, deep analysis",
+      "intelligence_score": 16,
+      "description": "DEPRECATED (shuts down June 17, 2026) - Gemini 2.5 Pro (1M context). Use gemini-3.1-pro-preview instead.",
       "context_window": 1048576,
       "max_output_tokens": 65536,
       "max_thinking_tokens": 32768,
@@ -66,18 +67,17 @@
       "supports_json_mode": true,
       "supports_images": true,
       "supports_temperature": true,
-      "allow_code_generation": true,
       "max_image_size_mb": 32.0
     },
     {
-      "model_name": "gemini-2.0-flash",
-      "friendly_name": "Gemini (Flash 2.0)",
+      "model_name": "gemini-3-flash-preview",
+      "friendly_name": "Gemini Flash 3.0 Preview",
       "aliases": [
-        "flash-2.0",
-        "flash2"
+        "flash3",
+        "gemini3-flash"
       ],
-      "intelligence_score": 9,
-      "description": "Gemini 2.0 Flash (1M context) - Latest fast model with experimental thinking, supports audio/video input",
+      "intelligence_score": 12,
+      "description": "Gemini 3 Flash (1M context, 65K output) - Fast reasoning with thinking_level support, vision, computer use",
       "context_window": 1048576,
       "max_output_tokens": 65536,
       "max_thinking_tokens": 24576,
@@ -91,23 +91,26 @@
       "max_image_size_mb": 20.0
     },
     {
-      "model_name": "gemini-2.0-flash-lite",
-      "friendly_name": "Gemini (Flash Lite 2.0)",
+      "model_name": "gemini-3.1-flash-lite-preview",
+      "friendly_name": "Gemini Flash Lite 3.1 Preview",
       "aliases": [
         "flashlite",
-        "flash-lite"
+        "flash-lite",
+        "lite"
       ],
-      "intelligence_score": 7,
-      "description": "Gemini 2.0 Flash Lite (1M context) - Lightweight fast model, text-only",
+      "intelligence_score": 9,
+      "description": "Gemini 3.1 Flash Lite (1M context, 65K output) - Cheapest Gemini model with thinking_level support",
       "context_window": 1048576,
       "max_output_tokens": 65536,
-      "supports_extended_thinking": false,
+      "max_thinking_tokens": 24576,
+      "supports_extended_thinking": true,
       "supports_system_prompts": true,
       "supports_streaming": true,
       "supports_function_calling": true,
       "supports_json_mode": true,
-      "supports_images": false,
-      "supports_temperature": true
+      "supports_images": true,
+      "supports_temperature": true,
+      "max_image_size_mb": 20.0
     },
     {
       "model_name": "gemini-2.5-flash",
@@ -117,7 +120,7 @@
         "flash2.5"
       ],
       "intelligence_score": 10,
-      "description": "Ultra-fast (1M context) - Quick analysis, simple queries, rapid iterations",
+      "description": "DEPRECATED (shuts down June 17, 2026) - Gemini 2.5 Flash (1M context). Use gemini-3-flash-preview instead.",
       "context_window": 1048576,
       "max_output_tokens": 65536,
       "max_thinking_tokens": 24576,
diff --git a/conf/openai_models.json b/conf/openai_models.json
index 327cfd18d..8f4c2f733 100644
--- a/conf/openai_models.json
+++ b/conf/openai_models.json
@@ -194,23 +194,117 @@
       "temperature_constraint": "fixed"
     },
     {
-      "model_name": "gpt-4.1",
-      "friendly_name": "OpenAI (GPT 4.1)",
+      "model_name": "gpt-5.4",
+      "friendly_name": "OpenAI (GPT-5.4)",
       "aliases": [
-        "gpt4.1"
+        "gpt5.4",
+        "gpt-5.4",
+        "5.4"
       ],
-      "intelligence_score": 13,
-      "description": "GPT-4.1 (1M context) - Advanced reasoning model with large context window",
-      "context_window": 1000000,
-      "max_output_tokens": 32768,
-      "supports_extended_thinking": false,
+      "intelligence_score": 19,
+      "description": "GPT-5.4 (1M context, 128K output) - March 2026 flagship with configurable reasoning effort and vision",
+      "context_window": 1050000,
+      "max_output_tokens": 128000,
+      "supports_extended_thinking": true,
+      "supports_system_prompts": true,
+      "supports_streaming": true,
+      "supports_function_calling": true,
+      "supports_json_mode": true,
+      "supports_images": true,
+      "supports_temperature": true,
+      "max_image_size_mb": 20.0,
+      "temperature_constraint": "fixed"
+    },
+    {
+      "model_name": "gpt-5.4-pro",
+      "friendly_name": "OpenAI (GPT-5.4 Pro)",
+      "aliases": [
+        "gpt5.4-pro",
+        "gpt5.4pro"
+      ],
+      "intelligence_score": 20,
+      "description": "GPT-5.4 Pro (1M context, 128K output) - Top-tier reasoning model, Responses API only",
+      "context_window": 1050000,
+      "max_output_tokens": 128000,
+      "supports_extended_thinking": true,
+      "supports_system_prompts": true,
+      "supports_streaming": false,
+      "supports_function_calling": true,
+      "supports_json_mode": true,
+      "supports_images": true,
+      "supports_temperature": true,
+      "max_image_size_mb": 20.0,
+      "use_openai_response_api": true,
+      "default_reasoning_effort": "high",
+      "allow_code_generation": true,
+      "temperature_constraint": "fixed"
+    },
+    {
+      "model_name": "gpt-5.4-mini",
+      "friendly_name": "OpenAI (GPT-5.4 Mini)",
+      "aliases": [
+        "gpt5.4-mini",
+        "gpt5.4mini"
+      ],
+      "intelligence_score": 16,
+      "description": "GPT-5.4 Mini (400K context, 128K output) - Cost-efficient 5.4 variant with full reasoning support",
+      "context_window": 400000,
+      "max_output_tokens": 128000,
+      "supports_extended_thinking": true,
       "supports_system_prompts": true,
       "supports_streaming": true,
       "supports_function_calling": true,
       "supports_json_mode": true,
       "supports_images": true,
       "supports_temperature": true,
-      "max_image_size_mb": 20.0
+      "max_image_size_mb": 20.0,
+      "temperature_constraint": "fixed"
+    },
+    {
+      "model_name": "gpt-5.4-nano",
+      "friendly_name": "OpenAI (GPT-5.4 Nano)",
+      "aliases": [
+        "gpt5.4-nano",
+        "gpt5.4nano"
+      ],
+      "intelligence_score": 14,
+      "description": "GPT-5.4 Nano (400K context, 128K output) - Fastest, cheapest 5.4 variant for high-throughput tasks",
+      "context_window": 400000,
+      "max_output_tokens": 128000,
+      "supports_extended_thinking": true,
+      "supports_system_prompts": true,
+      "supports_streaming": true,
+      "supports_function_calling": true,
+      "supports_json_mode": true,
+      "supports_images": true,
+      "supports_temperature": true,
+      "max_image_size_mb": 20.0,
+      "temperature_constraint": "fixed"
+    },
+    {
+      "model_name": "gpt-5.3-codex",
+      "friendly_name": "OpenAI (GPT-5.3 Codex)",
+      "aliases": [
+        "gpt5.3-codex",
+        "gpt-5.3-codex",
+        "codex-5.3"
+      ],
+      "intelligence_score": 19,
+      "description": "GPT-5.3 Codex (400K context, 128K output) - Agentic coding specialist, Responses API only",
+      "context_window": 400000,
+      "max_output_tokens": 128000,
+      "supports_extended_thinking": true,
+      "supports_system_prompts": true,
+      "supports_streaming": false,
+      "supports_function_calling": true,
+      "supports_json_mode": true,
+      "supports_images": true,
+      "supports_temperature": true,
+      "max_image_size_mb": 20.0,
+      "use_openai_response_api": true,
+      "default_reasoning_effort": "high",
+      "allow_code_generation": true,
+      "temperature_constraint": "fixed"
     },
     {
       "model_name": "gpt-5-codex",
diff --git a/conf/openrouter_models.json b/conf/openrouter_models.json
index e3b929db6..d32b851f1 100644
--- a/conf/openrouter_models.json
+++ b/conf/openrouter_models.json
@@ -103,12 +103,13 @@
       "intelligence_score": 8
     },
     {
-      "model_name": "google/gemini-3-pro-preview",
+      "model_name": "google/gemini-3.1-pro-preview",
       "aliases": [
         "pro",
         "gemini-pro",
         "gemini",
         "gemini3",
+        "gemini3.1",
         "pro-openrouter"
       ],
       "context_window": 1048576,
@@ -119,7 +120,7 @@
       "supports_images": true,
       "max_image_size_mb": 20.0,
       "allow_code_generation": true,
-      "description": "Google's Gemini 3.0 Pro via OpenRouter with vision",
+      "description": "Google's Gemini 3.1 Pro via OpenRouter with vision",
       "intelligence_score": 18
     },
     {
diff --git a/devenv.nix b/devenv.nix
new file mode 100644
index 000000000..662f18736
--- /dev/null
+++ b/devenv.nix
@@ -0,0 +1,44 @@
+{ pkgs, lib, ... }:
+# PAL MCP Server development environment
+#
+# Usage:
+#   1. Install devenv: https://devenv.sh/getting-started/
+#   2. Run `devenv shell` (or use direnv with the included .envrc)
+#   3. Set API keys via environment, .env file, or SecretSpec provider
+#   4. Run `./code_quality_checks.sh` to verify setup
+#
+# SecretSpec (optional):
+#   Create devenv.local.yaml to configure your secret provider:
+#     secretspec:
+#       enable: true
+#       provider: "onepassword://YourVault"
+{
+  languages.python = {
+    enable = true;
+    version = lib.strings.trim (builtins.readFile ./.python-version);
+    uv = {
+      enable = true;
+      sync = {
+        enable = true;
+        allGroups = false;
+        groups = [ "dev" ];
+      };
+    };
+    venv.enable = true;
+  };
+
+  # Lint tools provided via Nix to avoid dynamically linked binary issues
+  # on NixOS. Split into a separate dependency-group in pyproject.toml -
+  # on non-NixOS platforms, `uv sync --group lint` works too.
+  packages = with pkgs; [
+    ruff
+    black
+    isort
+    pre-commit
+  ];
+
+  env = {
+    DEFAULT_MODEL = "auto";
+    LOG_LEVEL = "DEBUG";
+  };
+}
diff --git a/devenv.yaml b/devenv.yaml
new file mode 100644
index 000000000..3bdedf62b
--- /dev/null
+++ b/devenv.yaml
@@ -0,0 +1,8 @@
+inputs:
+  nixpkgs:
+    url: github:NixOS/nixpkgs/nixpkgs-unstable
+  nixpkgs-python:
+    url: github:cachix/nixpkgs-python
+    inputs:
+      nixpkgs:
+        follows: nixpkgs
diff --git a/providers/base.py b/providers/base.py
index 6e334afad..3a584d331 100644
--- a/providers/base.py
+++ b/providers/base.py
@@ -3,7 +3,8 @@
 import logging
 import time
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, Any, Callable, Optional
+from collections.abc import Callable
+from typing import TYPE_CHECKING, Any
 
 if TYPE_CHECKING:
     from tools.models import ToolModelCategory
@@ -43,7 +44,7 @@ def __init__(self, api_key: str, **kwargs):
         """Initialize the provider with API key and optional configuration."""
         self.api_key = api_key
         self.config = kwargs
-        self._sorted_capabilities_cache: Optional[list[tuple[str, ModelCapabilities]]] = None
+        self._sorted_capabilities_cache: list[tuple[str, ModelCapabilities]] | None = None
 
     # ------------------------------------------------------------------
     # Provider identity & capability surface
@@ -148,9 +149,9 @@ def generate_content(
         self,
         prompt: str,
         model_name: str,
-        system_prompt: Optional[str] = None,
+        system_prompt: str | None = None,
         temperature: float = 0.3,
-        max_output_tokens: Optional[int] = None,
+        max_output_tokens: int | None = None,
         **kwargs,
     ) -> ModelResponse:
         """Generate content using the model.
@@ -244,7 +245,7 @@ def _run_with_retries(
         operation: Callable[[], Any],
         *,
         max_attempts: int,
-        delays: Optional[list[float]] = None,
+        delays: list[float] | None = None,
         log_prefix: str = "",
     ):
         """Execute ``operation`` with retry semantics.
@@ -267,7 +268,7 @@ def _run_with_retries(
 
         attempts = max_attempts
         delays = delays or []
-        last_exc: Optional[Exception] = None
+        last_exc: Exception | None = None
 
         for attempt_index in range(attempts):
             try:
@@ -340,12 +341,12 @@ def validate_parameters(self, model_name: str, temperature: float, **kwargs) ->
     # ------------------------------------------------------------------
     # Preference / registry hooks
     # ------------------------------------------------------------------
-    def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> Optional[str]:
+    def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> str | None:
         """Get the preferred model from this provider for a given category."""
 
         return None
 
-    def get_model_registry(self) -> Optional[dict[str, Any]]:
+    def get_model_registry(self) -> dict[str, Any] | None:
         """Return the model registry backing this provider, if any."""
 
         return None
@@ -356,8 +357,8 @@ def get_model_registry(self) -> Optional[dict[str, Any]]:
     def _lookup_capabilities(
         self,
         canonical_name: str,
-        requested_name: Optional[str] = None,
-    ) -> Optional[ModelCapabilities]:
+        requested_name: str | None = None,
+    ) -> ModelCapabilities | None:
         """Return ``ModelCapabilities`` for the canonical model name."""
 
         return self.get_all_model_capabilities().get(canonical_name)
diff --git a/providers/dial.py b/providers/dial.py
index bf96e3180..7f81fb260 100644
--- a/providers/dial.py
+++ b/providers/dial.py
@@ -2,7 +2,7 @@
 
 import logging
 import threading
-from typing import ClassVar, Optional
+from typing import ClassVar
 
 from utils.env import get_env
 
@@ -153,10 +153,10 @@ def generate_content(
         self,
         prompt: str,
         model_name: str,
-        system_prompt: Optional[str] = None,
+        system_prompt: str | None = None,
         temperature: float = 0.3,
-        max_output_tokens: Optional[int] = None,
-        images: Optional[list[str]] = None,
+        max_output_tokens: int | None = None,
+        images: list[str] | None = None,
         **kwargs,
     ) -> ModelResponse:
         """Generate content using DIAL's deployment-specific endpoint.
diff --git a/providers/gemini.py b/providers/gemini.py
index fc142c6ff..083c0cbc0 100644
--- a/providers/gemini.py
+++ b/providers/gemini.py
@@ -2,7 +2,7 @@
 
 import base64
 import logging
-from typing import TYPE_CHECKING, ClassVar, Optional
+from typing import TYPE_CHECKING, ClassVar
 
 if TYPE_CHECKING:
     from tools.models import ToolModelCategory
@@ -33,7 +33,7 @@ class GeminiModelProvider(RegistryBackedProviderMixin, ModelProvider):
     MODEL_CAPABILITIES: ClassVar[dict[str, ModelCapabilities]] = {}
 
     # Thinking mode configurations - percentages of model's max_thinking_tokens
-    # These percentages work across all models that support thinking
+    # Used for Gemini 2.x models that accept a numeric thinking_budget
     THINKING_BUDGETS = {
         "minimal": 0.005,  # 0.5% of max - minimal thinking for fast responses
         "low": 0.08,  # 8% of max - light reasoning tasks
@@ -42,6 +42,21 @@ class GeminiModelProvider(RegistryBackedProviderMixin, ModelProvider):
         "max": 1.0,  # 100% of max - full thinking budget
     }
 
+    # Gemini 3.x thinking levels - maps PAL mode names to Gemini API enum values
+    # 3.x uses thinking_level (enum) instead of thinking_budget (numeric)
+    THINKING_LEVELS_3X = {
+        "minimal": "MINIMAL",  # Only available on Flash models, not Pro
+        "low": "LOW",
+        "medium": "MEDIUM",
+        "high": "HIGH",
+        "max": "HIGH",  # Gemini 3.x caps at HIGH
+    }
+
+    @staticmethod
+    def _is_gemini_3x(model_name: str) -> bool:
+        """Return True if the model uses the Gemini 3.x thinking_level API."""
+        return model_name.startswith("gemini-3")
+
     def __init__(self, api_key: str, **kwargs):
         """Initialize Gemini provider with API key and optional base URL."""
         self._ensure_registry()
@@ -82,7 +97,7 @@ def client(self):
                 self._client = genai.Client(api_key=self.api_key)
         return self._client
 
-    def _resolve_http_timeout(self) -> Optional[float]:
+    def _resolve_http_timeout(self) -> float | None:
         """Compute timeout override from shared custom timeout environment variables."""
 
         timeouts: list[float] = []
@@ -115,11 +130,11 @@ def generate_content(
         self,
         prompt: str,
         model_name: str,
-        system_prompt: Optional[str] = None,
+        system_prompt: str | None = None,
         temperature: float = 1.0,
-        max_output_tokens: Optional[int] = None,
+        max_output_tokens: int | None = None,
         thinking_mode: str = "medium",
-        images: Optional[list[str]] = None,
+        images: list[str] | None = None,
         **kwargs,
     ) -> ModelResponse:
         """
@@ -173,14 +188,7 @@ def generate_content(
         # Create contents structure
         contents = [{"parts": parts}]
 
-        # Gemini 3 Pro Preview currently rejects medium thinking budgets; bump to high.
         effective_thinking_mode = thinking_mode
-        if resolved_model_name == "gemini-3-pro-preview" and thinking_mode == "medium":
-            logger.debug(
-                "Overriding thinking mode 'medium' with 'high' for %s due to launch limitation",
-                resolved_model_name,
-            )
-            effective_thinking_mode = "high"
 
         # Prepare generation config
         generation_config = types.GenerateContentConfig(
@@ -193,13 +201,22 @@ def generate_content(
             generation_config.max_output_tokens = max_output_tokens
 
         # Add thinking configuration for models that support it
-        if capabilities.supports_extended_thinking and effective_thinking_mode in self.THINKING_BUDGETS:
-            # Get model's max thinking tokens and calculate actual budget
-            model_config = capability_map.get(resolved_model_name)
-            if model_config and model_config.max_thinking_tokens > 0:
-                max_thinking_tokens = model_config.max_thinking_tokens
-                actual_thinking_budget = int(max_thinking_tokens * self.THINKING_BUDGETS[effective_thinking_mode])
-                generation_config.thinking_config = types.ThinkingConfig(thinking_budget=actual_thinking_budget)
+        if capabilities.supports_extended_thinking and effective_thinking_mode:
+            if self._is_gemini_3x(resolved_model_name):
+                # Gemini 3.x: use thinking_level enum instead of numeric budget
+                level = self.THINKING_LEVELS_3X.get(effective_thinking_mode)
+                if level:
+                    # Pro models don't support MINIMAL; fall back to LOW
+                    if level == "MINIMAL" and "pro" in resolved_model_name:
+                        level = "LOW"
+                    generation_config.thinking_config = types.ThinkingConfig(thinking_level=level)
+            elif effective_thinking_mode in self.THINKING_BUDGETS:
+                # Gemini 2.x: use numeric thinking_budget
+                model_config = capability_map.get(resolved_model_name)
+                if model_config and model_config.max_thinking_tokens > 0:
+                    max_thinking_tokens = model_config.max_thinking_tokens
+                    actual_thinking_budget = int(max_thinking_tokens * self.THINKING_BUDGETS[effective_thinking_mode])
+                    generation_config.thinking_config = types.ThinkingConfig(thinking_budget=actual_thinking_budget)
 
         # Retry logic with progressive delays
         max_retries = 4  # Total of 4 attempts
@@ -430,7 +447,7 @@ def _is_error_retryable(self, error: Exception) -> bool:
 
         return any(indicator in error_str for indicator in retryable_indicators)
 
-    def _process_image(self, image_path: str) -> Optional[dict]:
+    def _process_image(self, image_path: str) -> dict | None:
         """Process an image for Gemini API."""
         try:
             # Use base class validation
@@ -453,7 +470,7 @@ def _process_image(self, image_path: str) -> Optional[dict]:
             logger.error(f"Error processing image {image_path}: {e}")
             return None
 
-    def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> Optional[str]:
+    def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> str | None:
         """Get Gemini's preferred model for a given category from allowed models.
 
         Args:
@@ -471,7 +488,7 @@ def get_preferred_model(self, category: "ToolModelCategory", allowed_models: lis
         capability_map = self.get_all_model_capabilities()
 
         # Helper to find best model from candidates
-        def find_best(candidates: list[str]) -> Optional[str]:
+        def find_best(candidates: list[str]) -> str | None:
             """Return best model from candidates (sorted for consistency)."""
             return sorted(candidates, reverse=True)[0] if candidates else None
 
@@ -499,14 +516,18 @@ def find_best(candidates: list[str]) -> Optional[str]:
                 return find_best(pro_models)
 
         elif category == ToolModelCategory.FAST_RESPONSE:
-            # Prefer Flash models for speed
-            flash_models = [m for m in allowed_models if "flash" in m]
+            # Prefer Flash models (not Flash Lite) for speed
+            flash_models = [m for m in allowed_models if "flash" in m and "lite" not in m]
             if flash_models:
                 return find_best(flash_models)
+            # Fall back to Flash Lite
+            flash_lite = [m for m in allowed_models if "flash" in m and "lite" in m]
+            if flash_lite:
+                return find_best(flash_lite)
 
         # Default for BALANCED or as fallback
-        # Prefer Flash for balanced use, then Pro, then anything
-        flash_models = [m for m in allowed_models if "flash" in m]
+        # Prefer Flash (not Lite) for balanced use, then Pro, then anything
+        flash_models = [m for m in allowed_models if "flash" in m and "lite" not in m]
         if flash_models:
             return find_best(flash_models)
 
diff --git a/providers/openai.py b/providers/openai.py
index 2f96f5f8f..be8da2f51 100644
--- a/providers/openai.py
+++ b/providers/openai.py
@@ -1,7 +1,7 @@
 """OpenAI model provider implementation."""
 
 import logging
-from typing import TYPE_CHECKING, ClassVar, Optional
+from typing import TYPE_CHECKING, ClassVar
 
 if TYPE_CHECKING:
     from tools.models import ToolModelCategory
@@ -40,8 +40,8 @@ def __init__(self, api_key: str, **kwargs):
     def _lookup_capabilities(
         self,
         canonical_name: str,
-        requested_name: Optional[str] = None,
-    ) -> Optional[ModelCapabilities]:
+        requested_name: str | None = None,
+    ) -> ModelCapabilities | None:
         """Look up OpenAI capabilities from built-ins or the custom registry."""
 
         self._ensure_registry()
@@ -90,7 +90,7 @@ def get_provider_type(self) -> ProviderType:
     # Provider preferences
     # ------------------------------------------------------------------
 
-    def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> Optional[str]:
+    def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> str | None:
         """Get OpenAI's preferred model for a given category from allowed models.
 
         Args:
@@ -106,7 +106,7 @@ def get_preferred_model(self, category: "ToolModelCategory", allowed_models: lis
             return None
 
         # Helper to find first available from preference list
-        def find_first(preferences: list[str]) -> Optional[str]:
+        def find_first(preferences: list[str]) -> str | None:
             """Return first available model from preference list."""
             for model in preferences:
                 if model in allowed_models:
@@ -114,10 +114,12 @@ def find_first(preferences: list[str]) -> Optional[str]:
             return None
 
         if category == ToolModelCategory.EXTENDED_REASONING:
-            # Prefer models with extended thinking support
-            # GPT-5.1 Codex first for coding tasks
+            # Prefer models with strongest reasoning capabilities
             preferred = find_first(
                 [
+                    "gpt-5.4-pro",
+                    "gpt-5.3-codex",
+                    "gpt-5.4",
                     "gpt-5.1-codex",
                     "gpt-5.2",
                     "gpt-5-codex",
@@ -131,9 +133,11 @@ def find_first(preferences: list[str]) -> Optional[str]:
 
         elif category == ToolModelCategory.FAST_RESPONSE:
             # Prefer fast, cost-efficient models
-            # GPT-5.2 models for speed, GPT-5.1-Codex after (premium pricing but cached)
             preferred = find_first(
                 [
+                    "gpt-5.4-mini",
+                    "gpt-5.4-nano",
+                    "gpt-5.4",
                     "gpt-5.2",
                     "gpt-5.1-codex-mini",
                     "gpt-5",
@@ -147,9 +151,10 @@ def find_first(preferences: list[str]) -> Optional[str]:
 
         else:  # BALANCED or default
             # Prefer balanced performance/cost models
-            # Include GPT-5.2 family for latest capabilities
             preferred = find_first(
                 [
+                    "gpt-5.4",
+                    "gpt-5.4-mini",
                     "gpt-5.2",
                     "gpt-5.1-codex",
                     "gpt-5",
diff --git a/providers/openai_compatible.py b/providers/openai_compatible.py
index ccf4fac46..27b471423 100644
--- a/providers/openai_compatible.py
+++ b/providers/openai_compatible.py
@@ -3,7 +3,6 @@
 import copy
 import ipaddress
 import logging
-from typing import Optional
 from urllib.parse import urlparse
 
 from openai import OpenAI
@@ -103,7 +102,7 @@ def _ensure_model_allowed(
                         f"Model '{requested_name}' is not allowed by restriction policy. Allowed models: {sorted(self.allowed_models)}"
                     )
 
-    def _parse_allowed_models(self) -> Optional[set[str]]:
+    def _parse_allowed_models(self) -> set[str] | None:
         """Parse allowed models from environment variable.
 
         Returns:
@@ -390,8 +389,8 @@ def _generate_with_responses_endpoint(
         model_name: str,
         messages: list,
         temperature: float,
-        max_output_tokens: Optional[int] = None,
-        capabilities: Optional[ModelCapabilities] = None,
+        max_output_tokens: int | None = None,
+        capabilities: ModelCapabilities | None = None,
         **kwargs,
     ) -> ModelResponse:
         """Generate content using the /v1/responses endpoint for reasoning models."""
@@ -500,10 +499,10 @@ def generate_content(
         self,
         prompt: str,
         model_name: str,
-        system_prompt: Optional[str] = None,
+        system_prompt: str | None = None,
         temperature: float = 0.3,
-        max_output_tokens: Optional[int] = None,
-        images: Optional[list[str]] = None,
+        max_output_tokens: int | None = None,
+        images: list[str] | None = None,
         **kwargs,
     ) -> ModelResponse:
         """Generate content using the OpenAI-compatible API.
@@ -524,7 +523,7 @@ def generate_content(
         if not self.validate_model_name(model_name):
             raise ValueError(f"Model '{model_name}' not in allowed models list. Allowed models: {self.allowed_models}")
 
-        capabilities: Optional[ModelCapabilities]
+        capabilities: ModelCapabilities | None
         try:
             capabilities = self.get_capabilities(model_name)
         except Exception as exc:
@@ -830,7 +829,7 @@ def _is_error_retryable(self, error: Exception) -> bool:
 
         return any(indicator in error_str for indicator in retryable_indicators)
 
-    def _process_image(self, image_path: str) -> Optional[dict]:
+    def _process_image(self, image_path: str) -> dict | None:
         """Process an image for OpenAI-compatible API."""
         try:
             if image_path.startswith("data:"):
diff --git a/providers/registry.py b/providers/registry.py
index cd28c4266..368583a04 100644
--- a/providers/registry.py
+++ b/providers/registry.py
@@ -70,7 +70,7 @@ def register_provider(cls, provider_type: ProviderType, provider_class: type[Mod
         instance._initialized_providers.pop(provider_type, None)
 
     @classmethod
-    def get_provider(cls, provider_type: ProviderType, force_new: bool = False) -> Optional[ModelProvider]:
+    def get_provider(cls, provider_type: ProviderType, force_new: bool = False) -> ModelProvider | None:
         """Get an initialized provider instance.
 
         Args:
@@ -151,7 +151,7 @@ def get_provider(cls, provider_type: ProviderType, force_new: bool = False) -> O
         return provider
 
     @classmethod
-    def get_provider_for_model(cls, model_name: str) -> Optional[ModelProvider]:
+    def get_provider_for_model(cls, model_name: str) -> ModelProvider | None:
         """Get provider instance for a specific model name.
 
         Provider priority order:
@@ -301,7 +301,7 @@ def _collect_restricted_display_names(
         return display_names
 
     @classmethod
-    def get_available_model_names(cls, provider_type: Optional[ProviderType] = None) -> list[str]:
+    def get_available_model_names(cls, provider_type: ProviderType | None = None) -> list[str]:
         """Get list of available model names, optionally filtered by provider.
 
         This respects model restrictions automatically.
@@ -322,7 +322,7 @@ def get_available_model_names(cls, provider_type: Optional[ProviderType] = None)
             return list(available_models.keys())
 
     @classmethod
-    def _get_api_key_for_provider(cls, provider_type: ProviderType) -> Optional[str]:
+    def _get_api_key_for_provider(cls, provider_type: ProviderType) -> str | None:
         """Get API key for a provider from environment variables.
 
         Args:
@@ -366,8 +366,8 @@ def _get_allowed_models_for_provider(cls, provider: ModelProvider, provider_type
 
         # Get the provider's supported models
         try:
-            # Use list_models to get all supported models (handles both regular and custom providers)
-            supported_models = provider.list_models(respect_restrictions=False)
+            # Use list_models to get canonical model names only (aliases are for user input, not selection)
+            supported_models = provider.list_models(respect_restrictions=False, include_aliases=False)
         except (NotImplementedError, AttributeError):
             # Fallback to provider-declared capability maps if list_models not implemented
             model_map = getattr(provider, "MODEL_CAPABILITIES", None)
diff --git a/providers/shared/model_capabilities.py b/providers/shared/model_capabilities.py
index bd862fa97..0dbb2b427 100644
--- a/providers/shared/model_capabilities.py
+++ b/providers/shared/model_capabilities.py
@@ -2,7 +2,6 @@
 
 import math
 from dataclasses import dataclass, field
-from typing import Optional
 
 from .provider_type import ProviderType
 from .temperature import RangeTemperatureConstraint, TemperatureConstraint
@@ -53,7 +52,7 @@ class ModelCapabilities:
     supports_json_mode: bool = False
     supports_temperature: bool = True
     use_openai_response_api: bool = False
-    default_reasoning_effort: Optional[str] = None
+    default_reasoning_effort: str | None = None
     allow_code_generation: bool = (
         False  # Enables structured code generation in chat tool for substantial implementations
     )
@@ -64,7 +63,7 @@ class ModelCapabilities:
         default_factory=lambda: RangeTemperatureConstraint(0.0, 2.0, 0.3)
     )
 
-    def get_effective_temperature(self, requested_temperature: float) -> Optional[float]:
+    def get_effective_temperature(self, requested_temperature: float) -> float | None:
         """Return the temperature that should be sent to the provider.
 
         Models that do not support temperature return ``None`` so that callers
diff --git a/providers/shared/temperature.py b/providers/shared/temperature.py
index 22a54a98a..34dd7e39f 100644
--- a/providers/shared/temperature.py
+++ b/providers/shared/temperature.py
@@ -1,7 +1,6 @@
 """Helper types for validating model temperature parameters."""
 
 from abc import ABC, abstractmethod
-from typing import Optional
 
 __all__ = [
     "TemperatureConstraint",
@@ -83,7 +82,7 @@ def infer_support(model_name: str) -> tuple[bool, str]:
     @staticmethod
     def resolve_settings(
         model_name: str,
-        constraint_hint: Optional[str] = None,
+        constraint_hint: str | None = None,
     ) -> tuple[bool, "TemperatureConstraint", str]:
         """Derive temperature support and constraint for a model.
 
@@ -150,7 +149,7 @@ def get_default(self) -> float:
 class RangeTemperatureConstraint(TemperatureConstraint):
     """Constraint for providers that expose a continuous min/max temperature range."""
 
-    def __init__(self, min_temp: float, max_temp: float, default: Optional[float] = None):
+    def __init__(self, min_temp: float, max_temp: float, default: float | None = None):
         self.min_temp = min_temp
         self.max_temp = max_temp
         self.default_temp = default or (min_temp + max_temp) / 2
@@ -171,7 +170,7 @@ def get_default(self) -> float:
 class DiscreteTemperatureConstraint(TemperatureConstraint):
     """Constraint for models that permit a discrete list of temperature values."""
 
-    def __init__(self, allowed_values: list[float], default: Optional[float] = None):
+    def __init__(self, allowed_values: list[float], default: float | None = None):
         self.allowed_values = sorted(allowed_values)
         self.default_temp = default or allowed_values[len(allowed_values) // 2]
 
diff --git a/providers/xai.py b/providers/xai.py
index 82536da5f..97077b26f 100644
--- a/providers/xai.py
+++ b/providers/xai.py
@@ -1,7 +1,7 @@
 """X.AI (GROK) model provider implementation."""
 
 import logging
-from typing import TYPE_CHECKING, ClassVar, Optional
+from typing import TYPE_CHECKING, ClassVar
 
 if TYPE_CHECKING:
     from tools.models import ToolModelCategory
@@ -42,7 +42,7 @@ def get_provider_type(self) -> ProviderType:
         """Get the provider type."""
         return ProviderType.XAI
 
-    def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> Optional[str]:
+    def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> str | None:
         """Get XAI's preferred model for a given category from allowed models.
 
         Args:
diff --git a/pyproject.toml b/pyproject.toml
index c60506dc1..00051c877 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -2,7 +2,7 @@
 name = "pal-mcp-server"
 version = "9.8.2"
 description = "AI-powered MCP server with multiple model providers"
-requires-python = ">=3.9"
+requires-python = ">=3.12"
 dependencies = [
     "mcp>=1.0.0",
     "google-genai>=1.19.0",
@@ -11,6 +11,23 @@ dependencies = [
     "python-dotenv>=1.0.0",
 ]
 
+[dependency-groups]
+dev = [
+    "pytest>=7.4.0",
+    "pytest-asyncio>=0.21.0",
+    "pytest-mock>=3.11.0",
+    "python-semantic-release>=10.3.0",
+    "build>=1.0.0",
+]
+# AIDEV-NOTE: lint tools have native binaries that won't run on NixOS
+# when installed via uv. On NixOS, these are provided by Nix packages
+# in devenv.nix. On other platforms, sync this group: uv sync --group lint
+lint = [
+    "black>=23.0.0",
+    "ruff>=0.1.0",
+    "isort>=5.12.0",
+]
+
 [tool.setuptools.packages.find]
 include = ["tools*", "providers*", "systemprompts*", "utils*", "conf*", "clink*"]
 
@@ -40,7 +57,7 @@ pal-mcp-server = "server:run"
 
 [tool.black]
 line-length = 120
-target-version = ['py39', 'py310', 'py311', 'py312', 'py313']
+target-version = ['py312', 'py313']
 include = '\.pyi?$'
 extend-exclude = '''
 /(
@@ -68,10 +85,10 @@ force_grid_wrap = 0
 use_parentheses = true
 ensure_newline_before_comments = true
 line_length = 120
-skip_glob = ["venv/*", ".venv/*", ".pal_venv/*"]
+skip_glob = ["venv/*", ".venv/*", ".devenv/*"]
 
 [tool.ruff]
-target-version = "py39"
+target-version = "py312"
 line-length = 120
 
 [tool.ruff.lint]
@@ -89,6 +106,7 @@ ignore = [
     "B008",  # do not perform function calls in argument defaults
     "C901",  # too complex
     "B904",  # exception handling with raise from
+    "B905",  # zip() without strict= (upstream code)
 ]
 
 [tool.ruff.lint.per-file-ignores]
diff --git a/run_integration_tests.sh b/run_integration_tests.sh
index 6855cd1fb..17dd66e38 100755
--- a/run_integration_tests.sh
+++ b/run_integration_tests.sh
@@ -1,90 +1,51 @@
 #!/bin/bash
 
 # PAL MCP Server - Run Integration Tests
-# This script runs integration tests that require API keys
-# Run this locally on your Mac to ensure everything works end-to-end
+# This script runs integration tests that require API keys.
+#
+# Requires: devenv shell with secrets loaded via secretspec / use_op
 
 set -e  # Exit on any error
 
-echo "🧪 Running Integration Tests for PAL MCP Server"
+echo "Running Integration Tests for PAL MCP Server"
 echo "=============================================="
 echo "These tests use real API calls with your configured keys"
 echo ""
 
-# Activate virtual environment
-if [[ -f ".pal_venv/bin/activate" ]]; then
-    source .pal_venv/bin/activate
-    echo "✅ Using virtual environment"
-else
-    echo "❌ No virtual environment found!"
-    echo "Please run: ./run-server.sh first"
+# Ensure uv is available
+if ! command -v uv &> /dev/null; then
+    echo "Error: uv not found. Activate devenv first."
     exit 1
 fi
 
-# Check for .env file
-if [[ ! -f ".env" ]]; then
-    echo "⚠️  Warning: No .env file found. Integration tests may fail without API keys."
-    echo ""
-fi
-
-echo "🔑 Checking API key availability:"
+echo "Checking API key availability:"
 echo "---------------------------------"
 
-# Check which API keys are available
-if [[ -n "$GEMINI_API_KEY" ]] || grep -q "GEMINI_API_KEY=" .env 2>/dev/null; then
-    echo "✅ GEMINI_API_KEY configured"
-else
-    echo "❌ GEMINI_API_KEY not found"
-fi
-
-if [[ -n "$OPENAI_API_KEY" ]] || grep -q "OPENAI_API_KEY=" .env 2>/dev/null; then
-    echo "✅ OPENAI_API_KEY configured"
-else
-    echo "❌ OPENAI_API_KEY not found"
-fi
-
-if [[ -n "$XAI_API_KEY" ]] || grep -q "XAI_API_KEY=" .env 2>/dev/null; then
-    echo "✅ XAI_API_KEY configured"
-else
-    echo "❌ XAI_API_KEY not found"
-fi
-
-if [[ -n "$OPENROUTER_API_KEY" ]] || grep -q "OPENROUTER_API_KEY=" .env 2>/dev/null; then
-    echo "✅ OPENROUTER_API_KEY configured"
-else
-    echo "❌ OPENROUTER_API_KEY not found"
-fi
-
-if [[ -n "$CUSTOM_API_URL" ]] || grep -q "CUSTOM_API_URL=" .env 2>/dev/null; then
-    echo "✅ CUSTOM_API_URL configured (local models)"
-else
-    echo "❌ CUSTOM_API_URL not found"
-fi
+for key in GEMINI_API_KEY OPENAI_API_KEY XAI_API_KEY OPENROUTER_API_KEY CUSTOM_API_URL; do
+    if [[ -n "${!key}" ]]; then
+        echo "  $key configured"
+    else
+        echo "  $key not found"
+    fi
+done
 
 echo ""
 
 # Run integration tests
-echo "🏃 Running integration tests..."
+echo "Running integration tests..."
 echo "------------------------------"
 
-# Run only integration tests (marked with @pytest.mark.integration)
-python -m pytest tests/ -v -m "integration" --tb=short
+pytest tests/ -v -m "integration" --tb=short
 
 echo ""
-echo "✅ Integration tests completed!"
+echo "Integration tests completed!"
 echo ""
 
 # Also run simulator tests if requested
 if [[ "$1" == "--with-simulator" ]]; then
-    echo "🤖 Running simulator tests..."
+    echo "Running simulator tests..."
     echo "----------------------------"
     python communication_simulator_test.py --verbose
     echo ""
-    echo "✅ Simulator tests completed!"
+    echo "Simulator tests completed!"
 fi
-
-echo "💡 Tips:"
-echo "- Run './run_integration_tests.sh' for integration tests only"
-echo "- Run './run_integration_tests.sh --with-simulator' to also run simulator tests"
-echo "- Run './code_quality_checks.sh' for unit tests and linting"
-echo "- Check logs in logs/mcp_server.log if tests fail"
\ No newline at end of file
diff --git a/secretspec.toml b/secretspec.toml
new file mode 100644
index 000000000..35b6440d5
--- /dev/null
+++ b/secretspec.toml
@@ -0,0 +1,10 @@
+[project]
+name = "pal-mcp-server"
+revision = "1.0"
+
+[profiles.default]
+OPENAI_API_KEY = { description = "OpenAI API key", required = false }
+GEMINI_API_KEY = { description = "Google Gemini API key", required = false }
+ANTHROPIC_API_KEY = { description = "Anthropic API key", required = false }
+XAI_API_KEY = { description = "X.AI (Grok) API key", required = false }
+OPENROUTER_API_KEY = { description = "OpenRouter API key", required = false }
diff --git a/server.py b/server.py
index 74f7ed83f..385e88d5c 100644
--- a/server.py
+++ b/server.py
@@ -26,7 +26,7 @@
 import time
 from logging.handlers import RotatingFileHandler
 from pathlib import Path
-from typing import Any, Optional
+from typing import Any
 
 from mcp.server import Server  # noqa: E402
 from mcp.server.models import InitializationOptions  # noqa: E402
@@ -878,7 +878,7 @@ async def handle_call_tool(name: str, arguments: dict[str, Any]) -> list[TextCon
         return [TextContent(type="text", text=f"Unknown tool: {name}")]
 
 
-def parse_model_option(model_string: str) -> tuple[str, Optional[str]]:
+def parse_model_option(model_string: str) -> tuple[str, str | None]:
     """
     Parse model:option format into model name and option.
 
diff --git a/simulator_tests/base_test.py b/simulator_tests/base_test.py
index aa81e126e..93b6d70bc 100644
--- a/simulator_tests/base_test.py
+++ b/simulator_tests/base_test.py
@@ -9,7 +9,6 @@
 import logging
 import os
 import subprocess
-from typing import Optional
 
 from .log_utils import LogUtils
 
@@ -124,7 +123,7 @@ def multiply(self, a, b):
         self.test_files = {"python": os.path.abspath(test_py), "config": os.path.abspath(test_config)}
         self.logger.debug(f"Created test files with absolute paths: {list(self.test_files.values())}")
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool via standalone server"""
         try:
             # Prepare the MCP initialization and tool call sequence
@@ -198,7 +197,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
             self.logger.error(f"MCP tool call failed: {e}")
             return None, None
 
-    def _parse_mcp_response(self, stdout: str, expected_id: int = 2) -> Optional[str]:
+    def _parse_mcp_response(self, stdout: str, expected_id: int = 2) -> str | None:
         """Parse MCP JSON-RPC response from stdout"""
         try:
             lines = stdout.strip().split("\n")
@@ -234,7 +233,7 @@ def _parse_mcp_response(self, stdout: str, expected_id: int = 2) -> Optional[str
             self.logger.debug(f"Stdout that failed to parse: {stdout}")
             return None
 
-    def _extract_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from response metadata"""
         try:
             # Parse the response text as JSON to look for continuation metadata
@@ -298,7 +297,7 @@ def cleanup_test_files(self):
     # Log Utility Methods (delegate to LogUtils)
     # ============================================================================
 
-    def get_server_logs_since(self, since_time: Optional[str] = None) -> str:
+    def get_server_logs_since(self, since_time: str | None = None) -> str:
         """Get server logs from both main and activity log files."""
         return LogUtils.get_server_logs_since(since_time)
 
@@ -334,9 +333,7 @@ def validate_file_deduplication_in_logs(self, logs: str, tool_name: str, test_fi
         """Validate that logs show file deduplication behavior."""
         return LogUtils.validate_file_deduplication_in_logs(logs, tool_name, test_file)
 
-    def search_logs_for_pattern(
-        self, pattern: str, logs: Optional[str] = None, case_sensitive: bool = False
-    ) -> list[str]:
+    def search_logs_for_pattern(self, pattern: str, logs: str | None = None, case_sensitive: bool = False) -> list[str]:
         """Search logs for a specific pattern."""
         return LogUtils.search_logs_for_pattern(pattern, logs, case_sensitive)
 
diff --git a/simulator_tests/conversation_base_test.py b/simulator_tests/conversation_base_test.py
index f6d9388d0..1ce755007 100644
--- a/simulator_tests/conversation_base_test.py
+++ b/simulator_tests/conversation_base_test.py
@@ -36,7 +36,6 @@ def test_cross_tool_continuation(self):
 
 import asyncio
 import json
-from typing import Optional
 
 from tools.shared.exceptions import ToolExecutionError
 
@@ -106,7 +105,7 @@ def _get_event_loop(self):
                 asyncio.set_event_loop(self._loop)
         return self._loop
 
-    def call_mcp_tool_direct(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool_direct(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """
         Call an MCP tool directly in-process without subprocess isolation.
 
@@ -188,7 +187,7 @@ def call_mcp_tool_direct(self, tool_name: str, params: dict) -> tuple[Optional[s
             self.logger.error(f"Direct tool call failed for '{tool_name}': {e}")
             return None, None
 
-    def _extract_continuation_id_from_response(self, response_text: str) -> Optional[str]:
+    def _extract_continuation_id_from_response(self, response_text: str) -> str | None:
         """Extract continuation_id from tool response"""
         try:
             # Parse the response as JSON to look for continuation metadata
diff --git a/simulator_tests/log_utils.py b/simulator_tests/log_utils.py
index b25927e33..ccd5c8538 100644
--- a/simulator_tests/log_utils.py
+++ b/simulator_tests/log_utils.py
@@ -8,7 +8,6 @@
 import logging
 import re
 import subprocess
-from typing import Optional, Union
 
 
 class LogUtils:
@@ -19,7 +18,7 @@ class LogUtils:
     ACTIVITY_LOG_FILE = "logs/mcp_activity.log"
 
     @classmethod
-    def get_server_logs_since(cls, since_time: Optional[str] = None) -> str:
+    def get_server_logs_since(cls, since_time: str | None = None) -> str:
         """
         Get server logs from both main and activity log files.
 
@@ -204,7 +203,7 @@ def extract_thread_creation_logs(cls, logs: str) -> list[dict[str, str]]:
         return thread_data
 
     @classmethod
-    def extract_history_traversal_logs(cls, logs: str) -> list[dict[str, Union[str, int]]]:
+    def extract_history_traversal_logs(cls, logs: str) -> list[dict[str, str | int]]:
         """
         Extract conversation history traversal logs.
 
@@ -256,9 +255,7 @@ def validate_file_deduplication_in_logs(cls, logs: str, tool_name: str, test_fil
         return has_embedding and (has_filtering or has_skip) and has_tool_processing
 
     @classmethod
-    def search_logs_for_pattern(
-        cls, pattern: str, logs: Optional[str] = None, case_sensitive: bool = False
-    ) -> list[str]:
+    def search_logs_for_pattern(cls, pattern: str, logs: str | None = None, case_sensitive: bool = False) -> list[str]:
         """
         Search logs for a specific pattern.
 
@@ -283,7 +280,7 @@ def search_logs_for_pattern(
         return matches
 
     @classmethod
-    def get_log_file_info(cls) -> dict[str, dict[str, Union[str, int, bool]]]:
+    def get_log_file_info(cls) -> dict[str, dict[str, str | int | bool]]:
         """
         Get information about log files.
 
diff --git a/simulator_tests/test_analyze_validation.py b/simulator_tests/test_analyze_validation.py
index 968b020fa..2294e3fd1 100644
--- a/simulator_tests/test_analyze_validation.py
+++ b/simulator_tests/test_analyze_validation.py
@@ -8,7 +8,6 @@
 """
 
 import json
-from typing import Optional
 
 from .conversation_base_test import ConversationBaseTest
 
@@ -988,7 +987,7 @@ def _test_analysis_types(self) -> bool:
             self.logger.error(f"Analysis types test failed: {e}")
             return False
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool in-process - override for analyze-specific response handling"""
         # Use in-process implementation to maintain conversation memory
         response_text, _ = self.call_mcp_tool_direct(tool_name, params)
@@ -1001,7 +1000,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
 
         return response_text, continuation_id
 
-    def _extract_analyze_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_analyze_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from analyze response"""
         try:
             # Parse the response
diff --git a/simulator_tests/test_codereview_validation.py b/simulator_tests/test_codereview_validation.py
index 394b10ba0..27d2e1f44 100644
--- a/simulator_tests/test_codereview_validation.py
+++ b/simulator_tests/test_codereview_validation.py
@@ -8,7 +8,6 @@
 """
 
 import json
-from typing import Optional
 
 from .conversation_base_test import ConversationBaseTest
 
@@ -941,7 +940,7 @@ def _test_multi_step_file_context(self) -> bool:
             self.logger.error(f"Multi-step file context test failed: {e}")
             return False
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool in-process - override for codereview-specific response handling"""
         # Use in-process implementation to maintain conversation memory
         response_text, _ = self.call_mcp_tool_direct(tool_name, params)
@@ -954,7 +953,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
 
         return response_text, continuation_id
 
-    def _extract_review_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_review_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from codereview response"""
         try:
             # Parse the response
diff --git a/simulator_tests/test_debug_certain_confidence.py b/simulator_tests/test_debug_certain_confidence.py
index f8a41b29c..21bea9601 100644
--- a/simulator_tests/test_debug_certain_confidence.py
+++ b/simulator_tests/test_debug_certain_confidence.py
@@ -10,7 +10,6 @@
 """
 
 import json
-from typing import Optional
 
 from tools.shared.exceptions import ToolExecutionError
 
@@ -470,7 +469,7 @@ def _test_multi_step_investigation_certain(self) -> bool:
             self.logger.error(f"Multi-step investigation certain test failed: {e}")
             return False
 
-    def call_mcp_tool_direct(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool_direct(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool directly in-process to maintain conversation memory"""
         try:
             # Get the tool instance
@@ -507,7 +506,7 @@ def call_mcp_tool_direct(self, tool_name: str, params: dict) -> tuple[Optional[s
             self.logger.error(f"Failed to call tool '{tool_name}' directly: {e}")
             return None, None
 
-    def _extract_debug_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_debug_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from debug response"""
         try:
             response_data = json.loads(response_text)
diff --git a/simulator_tests/test_debug_validation.py b/simulator_tests/test_debug_validation.py
index 275a27acf..6c42124d3 100644
--- a/simulator_tests/test_debug_validation.py
+++ b/simulator_tests/test_debug_validation.py
@@ -8,7 +8,6 @@
 """
 
 import json
-from typing import Optional
 
 from .conversation_base_test import ConversationBaseTest
 
@@ -473,7 +472,7 @@ def _test_certain_confidence(self) -> bool:
             self.logger.error(f"Certain confidence test failed: {e}")
             return False
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool in-process - override for debug-specific response handling"""
         # Use in-process implementation to maintain conversation memory
         response_text, _ = self.call_mcp_tool_direct(tool_name, params)
@@ -486,7 +485,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
 
         return response_text, continuation_id
 
-    def _extract_debug_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_debug_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from debug response"""
         try:
             # Parse the response
diff --git a/simulator_tests/test_planner_continuation_history.py b/simulator_tests/test_planner_continuation_history.py
index 556c8bc1b..45e63845e 100644
--- a/simulator_tests/test_planner_continuation_history.py
+++ b/simulator_tests/test_planner_continuation_history.py
@@ -10,7 +10,6 @@
 """
 
 import json
-from typing import Optional
 
 from .conversation_base_test import ConversationBaseTest
 
@@ -328,7 +327,7 @@ def _test_context_accumulation(self) -> bool:
             self.logger.error(f"Context accumulation test failed: {e}")
             return False
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool in-process - override for planner-specific response handling"""
         # Use in-process implementation to maintain conversation memory
         response_text, _ = self.call_mcp_tool_direct(tool_name, params)
@@ -341,7 +340,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
 
         return response_text, continuation_id
 
-    def _extract_planner_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_planner_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from planner response"""
         try:
             # Parse the response - it's now direct JSON, not wrapped
diff --git a/simulator_tests/test_planner_validation.py b/simulator_tests/test_planner_validation.py
index 7d46e9a51..23373cdbc 100644
--- a/simulator_tests/test_planner_validation.py
+++ b/simulator_tests/test_planner_validation.py
@@ -9,7 +9,6 @@
 """
 
 import json
-from typing import Optional
 
 from .conversation_base_test import ConversationBaseTest
 
@@ -633,7 +632,7 @@ def _test_workflow_file_context(self) -> bool:
             self.logger.error(f"Workflow file context test failed: {e}")
             return False
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool in-process - override for planner-specific response handling"""
         # Use in-process implementation to maintain conversation memory
         response_text, _ = self.call_mcp_tool_direct(tool_name, params)
@@ -646,7 +645,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
 
         return response_text, continuation_id
 
-    def _extract_planner_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_planner_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from planner response"""
         try:
             # Parse the response
diff --git a/simulator_tests/test_planner_validation_old.py b/simulator_tests/test_planner_validation_old.py
index df1a22060..16840f66a 100644
--- a/simulator_tests/test_planner_validation_old.py
+++ b/simulator_tests/test_planner_validation_old.py
@@ -11,7 +11,6 @@
 """
 
 import json
-from typing import Optional
 
 from .conversation_base_test import ConversationBaseTest
 
@@ -313,7 +312,7 @@ def _test_branching_and_revision(self) -> bool:
             self.logger.error(f"Branching and revision test failed: {e}")
             return False
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool in-process - override for planner-specific response handling"""
         # Use in-process implementation to maintain conversation memory
         response_text, _ = self.call_mcp_tool_direct(tool_name, params)
@@ -326,7 +325,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
 
         return response_text, continuation_id
 
-    def _extract_planner_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_planner_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from planner response"""
         try:
             # Parse the response - it's now direct JSON, not wrapped
diff --git a/simulator_tests/test_precommitworkflow_validation.py b/simulator_tests/test_precommitworkflow_validation.py
index a6d8353b0..26b0507db 100644
--- a/simulator_tests/test_precommitworkflow_validation.py
+++ b/simulator_tests/test_precommitworkflow_validation.py
@@ -8,7 +8,6 @@
 """
 
 import json
-from typing import Optional
 
 from .conversation_base_test import ConversationBaseTest
 
@@ -524,7 +523,7 @@ def _test_certain_confidence(self) -> bool:
             self.logger.error(f"Certain confidence test failed: {e}")
             return False
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool in-process - override for precommit-specific response handling"""
         # Use in-process implementation to maintain conversation memory
         response_text, _ = self.call_mcp_tool_direct(tool_name, params)
@@ -537,7 +536,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
 
         return response_text, continuation_id
 
-    def _extract_precommit_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_precommit_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from precommit response"""
         try:
             # Parse the response
diff --git a/simulator_tests/test_refactor_validation.py b/simulator_tests/test_refactor_validation.py
index a67a10da6..8be4521fb 100644
--- a/simulator_tests/test_refactor_validation.py
+++ b/simulator_tests/test_refactor_validation.py
@@ -7,7 +7,6 @@
 """
 
 import json
-from typing import Optional
 
 from .conversation_base_test import ConversationBaseTest
 
@@ -945,7 +944,7 @@ def _test_different_refactor_types(self) -> bool:
             self.logger.error(f"Different refactor types test failed: {e}")
             return False
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool in-process - override for -specific response handling"""
         # Use in-process implementation to maintain conversation memory
         response_text, _ = self.call_mcp_tool_direct(tool_name, params)
@@ -958,7 +957,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
 
         return response_text, continuation_id
 
-    def _extract_refactor_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_refactor_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from refactor response"""
         try:
             # Parse the response
diff --git a/simulator_tests/test_secaudit_validation.py b/simulator_tests/test_secaudit_validation.py
index 8b906fe89..b6823eb29 100644
--- a/simulator_tests/test_secaudit_validation.py
+++ b/simulator_tests/test_secaudit_validation.py
@@ -226,7 +226,7 @@ def _test_single_audit_session(self) -> bool:
                     "next_step_required": True,
                     "findings": "Starting security assessment",
                     "relevant_files": [self.auth_file],
-                    "model": "gemini-2.0-flash-lite",
+                    "model": "gemini-3.1-flash-lite-preview",
                 },
             )
 
@@ -272,7 +272,7 @@ def _test_single_audit_session(self) -> bool:
                     ],
                     "confidence": "medium",
                     "continuation_id": continuation_id,
-                    "model": "gemini-2.0-flash-lite",
+                    "model": "gemini-3.1-flash-lite-preview",
                 },
             )
 
@@ -305,7 +305,7 @@ def _test_focused_security_audit(self) -> bool:
                     "security_scope": "Web API endpoints",
                     "threat_level": "high",
                     "audit_focus": "owasp",
-                    "model": "gemini-2.0-flash-lite",
+                    "model": "gemini-3.1-flash-lite-preview",
                 },
             )
 
@@ -346,7 +346,7 @@ def _test_complete_audit_with_analysis(self) -> bool:
                     "findings": "Starting OWASP Top 10 security assessment of authentication and API modules",
                     "relevant_files": [self.auth_file, self.api_file],
                     "security_scope": "Web application with authentication and API endpoints",
-                    "model": "gemini-2.0-flash-lite",
+                    "model": "gemini-3.1-flash-lite-preview",
                 },
             )
 
@@ -392,7 +392,7 @@ def _test_complete_audit_with_analysis(self) -> bool:
                     ],
                     "confidence": "high",
                     "continuation_id": continuation_id,
-                    "model": "gemini-2.0-flash-lite",
+                    "model": "gemini-3.1-flash-lite-preview",
                 },
             )
 
@@ -409,7 +409,7 @@ def _test_complete_audit_with_analysis(self) -> bool:
                     "relevant_files": [self.auth_file, self.api_file],
                     "confidence": "high",  # High confidence to trigger expert analysis
                     "continuation_id": continuation_id,
-                    "model": "gemini-2.0-flash-lite",
+                    "model": "gemini-3.1-flash-lite-preview",
                 },
             )
 
@@ -455,7 +455,7 @@ def _test_certain_confidence(self) -> bool:
                         {"severity": "critical", "description": "SQL injection vulnerability in login method"}
                     ],
                     "confidence": "certain",
-                    "model": "gemini-2.0-flash-lite",
+                    "model": "gemini-3.1-flash-lite-preview",
                 },
             )
 
@@ -500,7 +500,7 @@ def _test_continuation_with_chat(self) -> bool:
                     "next_step_required": True,
                     "findings": "Beginning authentication security analysis",
                     "relevant_files": [self.auth_file],
-                    "model": "gemini-2.0-flash-lite",
+                    "model": "gemini-3.1-flash-lite-preview",
                 },
             )
 
@@ -526,7 +526,7 @@ def _test_continuation_with_chat(self) -> bool:
                     {
                         "prompt": "Can you tell me more about the SQL injection vulnerability details found in the security audit?",
                         "continuation_id": continuation_id,
-                        "model": "gemini-2.0-flash-lite",
+                        "model": "gemini-3.1-flash-lite-preview",
                     },
                 )
 
@@ -562,7 +562,7 @@ def _test_model_selection(self) -> bool:
                     "findings": "Starting SSRF vulnerability analysis",
                     "relevant_files": [self.api_file],
                     "audit_focus": "owasp",
-                    "model": "gemini-2.0-flash-lite",
+                    "model": "gemini-3.1-flash-lite-preview",
                 },
             )
 
@@ -582,7 +582,7 @@ def _test_model_selection(self) -> bool:
                     "relevant_files": [self.auth_file],
                     "confidence": "high",
                     "use_assistant_model": False,  # Skip expert analysis
-                    "model": "gemini-2.0-flash-lite",
+                    "model": "gemini-3.1-flash-lite-preview",
                 },
             )
 
diff --git a/simulator_tests/test_testgen_validation.py b/simulator_tests/test_testgen_validation.py
index dfd1636f3..9836d8ea4 100644
--- a/simulator_tests/test_testgen_validation.py
+++ b/simulator_tests/test_testgen_validation.py
@@ -8,7 +8,6 @@
 """
 
 import json
-from typing import Optional
 
 from .conversation_base_test import ConversationBaseTest
 
@@ -430,7 +429,7 @@ def _test_certain_confidence(self) -> bool:
             self.logger.error(f"Certain confidence test failed: {e}")
             return False
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool in-process - override for testgen-specific response handling"""
         # Use in-process implementation to maintain conversation memory
         response_text, _ = self.call_mcp_tool_direct(tool_name, params)
@@ -443,7 +442,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
 
         return response_text, continuation_id
 
-    def _extract_testgen_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_testgen_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from testgen response"""
         try:
             # Parse the response
diff --git a/simulator_tests/test_thinkdeep_validation.py b/simulator_tests/test_thinkdeep_validation.py
index 038f08380..d69d7e967 100644
--- a/simulator_tests/test_thinkdeep_validation.py
+++ b/simulator_tests/test_thinkdeep_validation.py
@@ -8,7 +8,6 @@
 """
 
 import json
-from typing import Optional
 
 from .conversation_base_test import ConversationBaseTest
 
@@ -502,7 +501,7 @@ def _test_certain_confidence(self) -> bool:
             self.logger.error(f"Certain confidence test failed: {e}")
             return False
 
-    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
+    def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[str | None, str | None]:
         """Call an MCP tool in-process - override for thinkdeep-specific response handling"""
         # Use in-process implementation to maintain conversation memory
         response_text, _ = self.call_mcp_tool_direct(tool_name, params)
@@ -515,7 +514,7 @@ def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Op
 
         return response_text, continuation_id
 
-    def _extract_thinkdeep_continuation_id(self, response_text: str) -> Optional[str]:
+    def _extract_thinkdeep_continuation_id(self, response_text: str) -> str | None:
         """Extract continuation_id from thinkdeep response"""
         try:
             # Parse the response
diff --git a/tests/http_transport_recorder.py b/tests/http_transport_recorder.py
index 4bc13eb04..48174e495 100644
--- a/tests/http_transport_recorder.py
+++ b/tests/http_transport_recorder.py
@@ -18,7 +18,7 @@
 import json
 import logging
 from pathlib import Path
-from typing import Any, Optional
+from typing import Any
 
 import httpx
 
@@ -278,7 +278,7 @@ def _handle_request(self, request: httpx.Request) -> httpx.Response:
             request=request,
         )
 
-    def _find_matching_interaction(self, request: httpx.Request) -> Optional[dict[str, Any]]:
+    def _find_matching_interaction(self, request: httpx.Request) -> dict[str, Any] | None:
         """Find interaction that matches the request."""
         request_signature = self._get_request_signature(request)
 
@@ -409,7 +409,7 @@ def create_transport(cassette_path: str) -> httpx.HTTPTransport:
             return RecordingTransport(cassette_path)
 
     @staticmethod
-    def should_record(cassette_path: str, api_key: Optional[str] = None) -> bool:
+    def should_record(cassette_path: str, api_key: str | None = None) -> bool:
         """Determine if we should record based on cassette and API key availability."""
         cassette_file = Path(cassette_path)
 
diff --git a/tests/pii_sanitizer.py b/tests/pii_sanitizer.py
index 94615e9d6..72633cfb9 100644
--- a/tests/pii_sanitizer.py
+++ b/tests/pii_sanitizer.py
@@ -12,7 +12,7 @@
 from copy import deepcopy
 from dataclasses import dataclass
 from re import Pattern
-from typing import Any, Optional
+from typing import Any
 
 logger = logging.getLogger(__name__)
 
@@ -35,7 +35,7 @@ def create(cls, name: str, pattern: str, replacement: str, description: str) ->
 class PIISanitizer:
     """Sanitizes PII from various data structures while preserving format."""
 
-    def __init__(self, patterns: Optional[list[PIIPattern]] = None):
+    def __init__(self, patterns: list[PIIPattern] | None = None):
         """Initialize with optional custom patterns."""
         self.patterns: list[PIIPattern] = patterns or []
         self.sanitize_enabled = True
diff --git a/tests/test_auto_mode_comprehensive.py b/tests/test_auto_mode_comprehensive.py
index c06afba97..1af6e3787 100644
--- a/tests/test_auto_mode_comprehensive.py
+++ b/tests/test_auto_mode_comprehensive.py
@@ -80,9 +80,9 @@ def teardown_method(self):
                     "OPENROUTER_API_KEY": None,
                 },
                 {
-                    "EXTENDED_REASONING": "gemini-3-pro-preview",  # Gemini 3 Pro Preview for deep thinking
-                    "FAST_RESPONSE": "gemini-2.5-flash",  # Flash for speed
-                    "BALANCED": "gemini-2.5-flash",  # Flash as balanced
+                    "EXTENDED_REASONING": "gemini-3.1-pro-preview",  # Gemini 3.1 Pro Preview for deep thinking
+                    "FAST_RESPONSE": "gemini-3-flash-preview",  # Flash preview for speed
+                    "BALANCED": "gemini-3-flash-preview",  # Flash preview as balanced
                 },
             ),
             # Only OpenAI API available
@@ -94,9 +94,9 @@ def teardown_method(self):
                     "OPENROUTER_API_KEY": None,
                 },
                 {
-                    "EXTENDED_REASONING": "gpt-5.1-codex",  # GPT-5.1 Codex prioritized for coding tasks
-                    "FAST_RESPONSE": "gpt-5.2",  # Prefer gpt-5.2 for speed
-                    "BALANCED": "gpt-5.2",  # Prefer gpt-5.2 for balanced
+                    "EXTENDED_REASONING": "gpt-5.4-pro",  # GPT-5.4 Pro prioritized for reasoning tasks
+                    "FAST_RESPONSE": "gpt-5.4-mini",  # Prefer gpt-5.4-mini for speed
+                    "BALANCED": "gpt-5.4",  # Prefer gpt-5.4 for balanced
                 },
             ),
             # Only X.AI API available
@@ -122,9 +122,9 @@ def teardown_method(self):
                     "OPENROUTER_API_KEY": None,
                 },
                 {
-                    "EXTENDED_REASONING": "gemini-3-pro-preview",  # Gemini 3 Pro Preview comes first in priority
-                    "FAST_RESPONSE": "gemini-2.5-flash",  # Prefer flash for speed
-                    "BALANCED": "gemini-2.5-flash",  # Prefer flash for balanced
+                    "EXTENDED_REASONING": "gemini-3.1-pro-preview",  # Gemini 3.1 Pro Preview comes first in priority
+                    "FAST_RESPONSE": "gemini-3-flash-preview",  # Prefer flash preview for speed
+                    "BALANCED": "gemini-3-flash-preview",  # Prefer flash preview for balanced
                 },
             ),
             # All native APIs available - Google still comes first
@@ -136,9 +136,9 @@ def teardown_method(self):
                     "OPENROUTER_API_KEY": None,
                 },
                 {
-                    "EXTENDED_REASONING": "gemini-3-pro-preview",  # Gemini 3 Pro Preview comes first in priority
-                    "FAST_RESPONSE": "gemini-2.5-flash",  # Prefer flash for speed
-                    "BALANCED": "gemini-2.5-flash",  # Prefer flash for balanced
+                    "EXTENDED_REASONING": "gemini-3.1-pro-preview",  # Gemini 3.1 Pro Preview comes first in priority
+                    "FAST_RESPONSE": "gemini-3-flash-preview",  # Prefer flash preview for speed
+                    "BALANCED": "gemini-3-flash-preview",  # Prefer flash preview for balanced
                 },
             ),
         ],
diff --git a/tests/test_auto_mode_provider_selection.py b/tests/test_auto_mode_provider_selection.py
index fc2c8d2ba..7a22b4816 100644
--- a/tests/test_auto_mode_provider_selection.py
+++ b/tests/test_auto_mode_provider_selection.py
@@ -59,9 +59,9 @@ def test_gemini_only_fallback_selection(self):
             balanced = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.BALANCED)
 
             # Should select appropriate Gemini models
-            assert extended_reasoning in ["gemini-3-pro-preview", "gemini-2.5-pro", "pro"]
-            assert fast_response in ["gemini-2.5-flash", "flash"]
-            assert balanced in ["gemini-2.5-flash", "flash"]
+            assert extended_reasoning in ["gemini-3.1-pro-preview", "gemini-2.5-pro", "pro"]
+            assert fast_response in ["gemini-3-flash-preview", "gemini-2.5-flash", "flash"]
+            assert balanced in ["gemini-3-flash-preview", "gemini-2.5-flash", "flash"]
 
         finally:
             # Restore original environment
@@ -98,9 +98,9 @@ def test_openai_only_fallback_selection(self):
             balanced = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.BALANCED)
 
             # Should select appropriate OpenAI models based on new preference order
-            assert extended_reasoning == "gpt-5.1-codex"  # GPT-5.1 Codex prioritized for extended reasoning
-            assert fast_response == "gpt-5.2"  # gpt-5.2 comes first in fast response preference
-            assert balanced == "gpt-5.2"  # gpt-5.2 for balanced
+            assert extended_reasoning == "gpt-5.4-pro"  # GPT-5.4 Pro prioritized for extended reasoning
+            assert fast_response == "gpt-5.4-mini"  # gpt-5.4-mini comes first in fast response preference
+            assert balanced == "gpt-5.4"  # gpt-5.4 for balanced
 
         finally:
             # Restore original environment
@@ -139,10 +139,10 @@ def test_both_gemini_and_openai_priority(self):
             fast_response = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.FAST_RESPONSE)
 
             # Should prefer Gemini now (based on new provider priority: Gemini before OpenAI)
-            assert extended_reasoning == "gemini-3-pro-preview"  # Gemini 3 Pro Preview has higher priority now
+            assert extended_reasoning == "gemini-3.1-pro-preview"  # Gemini 3.1 Pro Preview has higher priority now
 
             # Should prefer Gemini for fast response
-            assert fast_response == "gemini-2.5-flash"  # Gemini has higher priority now
+            assert fast_response == "gemini-3-flash-preview"  # Gemini has higher priority now
 
         finally:
             # Restore original environment
@@ -317,7 +317,7 @@ def test_alias_resolution_before_api_calls(self):
             # Test that providers resolve aliases correctly
             test_cases = [
                 ("flash", ProviderType.GOOGLE, "gemini-2.5-flash"),
-                ("pro", ProviderType.GOOGLE, "gemini-3-pro-preview"),  # "pro" now resolves to gemini-3-pro-preview
+                ("pro", ProviderType.GOOGLE, "gemini-3.1-pro-preview"),  # "pro" now resolves to gemini-3.1-pro-preview
                 ("mini", ProviderType.OPENAI, "gpt-5-mini"),  # "mini" now resolves to gpt-5-mini
                 ("o3mini", ProviderType.OPENAI, "o3-mini"),
                 ("grok", ProviderType.XAI, "grok-4"),
diff --git a/tests/test_docker_volume_persistence.py b/tests/test_docker_volume_persistence.py
index 9d93453b9..ea63f5b20 100644
--- a/tests/test_docker_volume_persistence.py
+++ b/tests/test_docker_volume_persistence.py
@@ -125,7 +125,7 @@ class TestDockerVolumeIntegration:
 
     def test_mcp_config_persistence(self):
         """Test that MCP configuration persists in named volume"""
-        mcp_config = {"models": ["gemini-2.0-flash", "gpt-4"], "default_model": "auto", "thinking_mode": "high"}
+        mcp_config = {"models": ["gemini-2.5-flash", "gpt-4"], "default_model": "auto", "thinking_mode": "high"}
 
         # Test config serialization/deserialization
         config_str = json.dumps(mcp_config)
diff --git a/tests/test_intelligent_fallback.py b/tests/test_intelligent_fallback.py
index fe552a0b2..a19b6f012 100644
--- a/tests/test_intelligent_fallback.py
+++ b/tests/test_intelligent_fallback.py
@@ -37,25 +37,25 @@ def teardown_method(self):
 
     @patch.dict(os.environ, {"OPENAI_API_KEY": "sk-test-key", "GEMINI_API_KEY": ""}, clear=False)
     def test_prefers_openai_o3_mini_when_available(self):
-        """Test that gpt-5.2 is preferred when OpenAI API key is available (based on new preference order)"""
+        """Test that gpt-5.4 is preferred when OpenAI API key is available (based on new preference order)"""
         # Register only OpenAI provider for this test
         from providers.openai import OpenAIModelProvider
 
         ModelProviderRegistry.register_provider(ProviderType.OPENAI, OpenAIModelProvider)
 
         fallback_model = ModelProviderRegistry.get_preferred_fallback_model()
-        assert fallback_model == "gpt-5.2"  # Based on new preference order: gpt-5.2 before o4-mini
+        assert fallback_model == "gpt-5.4"  # Based on new preference order: gpt-5.4 before gpt-5.2
 
     @patch.dict(os.environ, {"OPENAI_API_KEY": "", "GEMINI_API_KEY": "test-gemini-key"}, clear=False)
     def test_prefers_gemini_flash_when_openai_unavailable(self):
-        """Test that gemini-2.5-flash is used when only Gemini API key is available"""
+        """Test that gemini-3-flash-preview is used when only Gemini API key is available"""
         # Register only Gemini provider for this test
         from providers.gemini import GeminiModelProvider
 
         ModelProviderRegistry.register_provider(ProviderType.GOOGLE, GeminiModelProvider)
 
         fallback_model = ModelProviderRegistry.get_preferred_fallback_model()
-        assert fallback_model == "gemini-2.5-flash"
+        assert fallback_model == "gemini-3-flash-preview"
 
     @patch.dict(os.environ, {"OPENAI_API_KEY": "sk-test-key", "GEMINI_API_KEY": "test-gemini-key"}, clear=False)
     def test_prefers_openai_when_both_available(self):
@@ -68,7 +68,7 @@ def test_prefers_openai_when_both_available(self):
         ModelProviderRegistry.register_provider(ProviderType.GOOGLE, GeminiModelProvider)
 
         fallback_model = ModelProviderRegistry.get_preferred_fallback_model()
-        assert fallback_model == "gemini-2.5-flash"  # Gemini has priority now (based on new PROVIDER_PRIORITY_ORDER)
+        assert fallback_model == "gemini-3-flash-preview"  # Gemini has priority now (based on new PROVIDER_PRIORITY_ORDER)
 
     @patch.dict(os.environ, {"OPENAI_API_KEY": "", "GEMINI_API_KEY": ""}, clear=False)
     def test_fallback_when_no_keys_available(self):
@@ -147,8 +147,8 @@ def test_auto_mode_conversation_memory_integration(self):
 
                 history, tokens = build_conversation_history(context, model_context=None)
 
-                # Verify that ModelContext was called with gpt-5.2 (the intelligent fallback based on new preference order)
-                mock_context_class.assert_called_once_with("gpt-5.2")
+                # Verify that ModelContext was called with gpt-5.4 (the intelligent fallback based on new preference order)
+                mock_context_class.assert_called_once_with("gpt-5.4")
 
     def test_auto_mode_with_gemini_only(self):
         """Test auto mode behavior when only Gemini API key is available"""
@@ -186,8 +186,8 @@ def test_auto_mode_with_gemini_only(self):
 
                 history, tokens = build_conversation_history(context, model_context=None)
 
-                # Should use gemini-2.5-flash when only Gemini is available
-                mock_context_class.assert_called_once_with("gemini-2.5-flash")
+                # Should use gemini-3-flash-preview when only Gemini is available
+                mock_context_class.assert_called_once_with("gemini-3-flash-preview")
 
     def test_non_auto_mode_unchanged(self):
         """Test that non-auto mode behavior is unchanged"""
diff --git a/tests/test_listmodels.py b/tests/test_listmodels.py
index 8375489e6..d3695ddf8 100644
--- a/tests/test_listmodels.py
+++ b/tests/test_listmodels.py
@@ -66,7 +66,7 @@ async def test_execute_with_gemini_configured(self, tool):
             # Check Gemini shows as configured
             assert "Google Gemini ✅" in content
             assert "`flash` → `gemini-2.5-flash`" in content
-            assert "`pro` → `gemini-3-pro-preview`" in content
+            assert "`pro` → `gemini-3.1-pro-preview`" in content
             assert "1M context" in content
             assert "Supports structured code generation" in content
 
diff --git a/tests/test_model_resolution_bug.py b/tests/test_model_resolution_bug.py
index 6c3cf0347..194328fe7 100644
--- a/tests/test_model_resolution_bug.py
+++ b/tests/test_model_resolution_bug.py
@@ -22,21 +22,21 @@ def setup_method(self):
         self.consensus_tool = ConsensusTool()
 
     def test_openrouter_registry_resolves_gemini_alias(self):
-        """Test that OpenRouter registry properly resolves 'gemini' to 'google/gemini-3-pro-preview'."""
+        """Test that OpenRouter registry properly resolves 'gemini' to 'google/gemini-3.1-pro-preview'."""
         # Test the registry directly
         provider = OpenRouterProvider("test_key")
 
         # Test alias resolution
         resolved_model_name = provider._resolve_model_name("gemini")
         assert (
-            resolved_model_name == "google/gemini-3-pro-preview"
-        ), f"Expected 'google/gemini-3-pro-preview', got '{resolved_model_name}'"
+            resolved_model_name == "google/gemini-3.1-pro-preview"
+        ), f"Expected 'google/gemini-3.1-pro-preview', got '{resolved_model_name}'"
 
         # Test that it also works with 'pro' alias
         resolved_pro = provider._resolve_model_name("pro")
         assert (
-            resolved_pro == "google/gemini-3-pro-preview"
-        ), f"Expected 'google/gemini-3-pro-preview', got '{resolved_pro}'"
+            resolved_pro == "google/gemini-3.1-pro-preview"
+        ), f"Expected 'google/gemini-3.1-pro-preview', got '{resolved_pro}'"
 
     # DELETED: test_provider_registry_returns_openrouter_for_gemini
     # This test had a flawed mock setup - it mocked get_provider() but called get_provider_for_model().
diff --git a/tests/test_model_restrictions.py b/tests/test_model_restrictions.py
index e2b98b105..1bcd9d392 100644
--- a/tests/test_model_restrictions.py
+++ b/tests/test_model_restrictions.py
@@ -74,7 +74,7 @@ def fake_get_provider(provider_type, force_new=False):
                 # Check Google models
                 assert service.is_allowed(ProviderType.GOOGLE, "flash")
                 assert service.is_allowed(ProviderType.GOOGLE, "pro")
-                assert service.is_allowed(ProviderType.GOOGLE, "gemini-3-pro-preview")
+                assert service.is_allowed(ProviderType.GOOGLE, "gemini-3.1-pro-preview")
 
     def test_case_insensitive_and_whitespace_handling(self):
         """Test that model names are case-insensitive and whitespace is trimmed."""
diff --git a/tests/test_o3_temperature_fix_simple.py b/tests/test_o3_temperature_fix_simple.py
index 81b9f796e..b929b64ae 100644
--- a/tests/test_o3_temperature_fix_simple.py
+++ b/tests/test_o3_temperature_fix_simple.py
@@ -79,7 +79,7 @@ def test_regular_models_include_temperature_in_api_call(self, mock_openai_class,
         mock_response.choices = [Mock()]
         mock_response.choices[0].message.content = "Test response"
         mock_response.choices[0].finish_reason = "stop"
-        mock_response.model = "gpt-4.1-2025-04-14"
+        mock_response.model = "gpt-5.4"
         mock_response.id = "test-id"
         mock_response.created = 1234567890
         mock_response.usage = Mock()
@@ -97,18 +97,16 @@ def test_regular_models_include_temperature_in_api_call(self, mock_openai_class,
         # Override model validation to bypass restrictions
         provider.validate_model_name = lambda name: True
 
-        # Call generate_content with regular model (use supported model)
-        provider.generate_content(
-            prompt="Test prompt", model_name="gpt-4.1-2025-04-14", temperature=0.5, max_output_tokens=100
-        )
+        # Call generate_content with regular model (gpt-5.4 has fixed temperature=1.0)
+        provider.generate_content(prompt="Test prompt", model_name="gpt-5.4", temperature=1.0, max_output_tokens=100)
 
         # Verify the API call was made WITH temperature and max_tokens
         mock_client.chat.completions.create.assert_called_once()
         call_kwargs = mock_client.chat.completions.create.call_args[1]
 
-        assert call_kwargs["temperature"] == 0.5, "Regular models should include temperature parameter"
+        assert call_kwargs["temperature"] == 1.0, "Regular models should include temperature parameter"
         assert call_kwargs["max_tokens"] == 100, "Regular models should include max_tokens parameter"
-        assert call_kwargs["model"] == "gpt-4.1-2025-04-14"
+        assert call_kwargs["model"] == "gpt-5.4"
 
     @patch("utils.model_restrictions.get_restriction_service")
     @patch("providers.openai_compatible.OpenAI")
@@ -195,7 +193,7 @@ def test_all_o3_models_have_correct_temperature_capability(self, mock_restrictio
             assert capabilities.supports_temperature is False, f"Model {model} should have supports_temperature=False"
 
         # Test that regular models DO support temperature parameter
-        regular_models = ["gpt-4.1-2025-04-14"]
+        regular_models = ["gpt-5.4"]
 
         for model in regular_models:
             try:
@@ -229,11 +227,11 @@ def test_openai_provider_temperature_constraints(self, mock_restriction_service)
         assert temp_constraint.validate(1.0) is True
         assert temp_constraint.validate(0.5) is False
 
-        # Test regular model constraints - use gpt-4.1 which is supported
-        gpt41_capabilities = provider.get_capabilities("gpt-4.1")
-        assert gpt41_capabilities.temperature_constraint is not None
+        # Test GPT-5.4 constraints - also fixed temperature but supports_temperature=true
+        gpt54_capabilities = provider.get_capabilities("gpt-5.4")
+        assert gpt54_capabilities.temperature_constraint is not None
 
-        # Regular models should allow a range
-        temp_constraint = gpt41_capabilities.temperature_constraint
-        assert temp_constraint.validate(0.5) is True
+        # GPT-5.4 has fixed temperature=1.0 (like O3) but still sends it in the API call
+        temp_constraint = gpt54_capabilities.temperature_constraint
         assert temp_constraint.validate(1.0) is True
+        assert temp_constraint.validate(0.5) is False
diff --git a/tests/test_openai_provider.py b/tests/test_openai_provider.py
index 66faf583f..388ec2715 100644
--- a/tests/test_openai_provider.py
+++ b/tests/test_openai_provider.py
@@ -207,7 +207,7 @@ def test_generate_content_resolves_alias_before_api_call(self, mock_openai_class
         mock_response.choices = [MagicMock()]
         mock_response.choices[0].message.content = "Test response"
         mock_response.choices[0].finish_reason = "stop"
-        mock_response.model = "gpt-4.1-2025-04-14"  # API returns the resolved model name
+        mock_response.model = "gpt-5.4"  # API returns the resolved model name
         mock_response.id = "test-id"
         mock_response.created = 1234567890
         mock_response.usage = MagicMock()
@@ -219,21 +219,21 @@ def test_generate_content_resolves_alias_before_api_call(self, mock_openai_class
 
         provider = OpenAIModelProvider("test-key")
 
-        # Call generate_content with alias 'gpt4.1' (resolves to gpt-4.1, supports temperature)
+        # Call generate_content with alias 'gpt5.4' (resolves to gpt-5.4, supports temperature)
         result = provider.generate_content(
             prompt="Test prompt",
-            model_name="gpt4.1",
-            temperature=1.0,  # This should be resolved to "gpt-4.1"
+            model_name="gpt5.4",
+            temperature=1.0,  # This should be resolved to "gpt-5.4"
         )
 
         # Verify the API was called with the RESOLVED model name
         mock_client.chat.completions.create.assert_called_once()
         call_kwargs = mock_client.chat.completions.create.call_args[1]
 
-        # CRITICAL ASSERTION: The API should receive "gpt-4.1", not "gpt4.1"
-        assert call_kwargs["model"] == "gpt-4.1", f"Expected 'gpt-4.1' but API received '{call_kwargs['model']}'"
+        # CRITICAL ASSERTION: The API should receive "gpt-5.4", not "gpt5.4"
+        assert call_kwargs["model"] == "gpt-5.4", f"Expected 'gpt-5.4' but API received '{call_kwargs['model']}'"
 
-        # Verify other parameters (gpt-4.1 supports temperature unlike O3/O4 models)
+        # Verify other parameters (gpt-5.4 supports temperature unlike O3/O4 models)
         assert call_kwargs["temperature"] == 1.0
         assert len(call_kwargs["messages"]) == 1
         assert call_kwargs["messages"][0]["role"] == "user"
@@ -241,7 +241,7 @@ def test_generate_content_resolves_alias_before_api_call(self, mock_openai_class
 
         # Verify response
         assert result.content == "Test response"
-        assert result.model_name == "gpt-4.1"  # Should be the resolved name
+        assert result.model_name == "gpt-5.4"  # Should be the resolved name
 
     @patch("providers.openai_compatible.OpenAI")
     def test_generate_content_other_aliases(self, mock_openai_class):
diff --git a/tests/test_per_tool_model_defaults.py b/tests/test_per_tool_model_defaults.py
index 3da4e30a2..449733f2c 100644
--- a/tests/test_per_tool_model_defaults.py
+++ b/tests/test_per_tool_model_defaults.py
@@ -98,8 +98,8 @@ def test_extended_reasoning_with_openai(self):
             ModelProviderRegistry.register_provider(ProviderType.OPENAI, OpenAIModelProvider)
 
             model = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.EXTENDED_REASONING)
-            # OpenAI prefers GPT-5.1-Codex for extended reasoning (coding tasks)
-            assert model == "gpt-5.1-codex"
+            # OpenAI prefers GPT-5.4 Pro for extended reasoning
+            assert model == "gpt-5.4-pro"
 
     def test_extended_reasoning_with_gemini_only(self):
         """Test EXTENDED_REASONING prefers pro when only Gemini is available."""
@@ -116,8 +116,8 @@ def test_extended_reasoning_with_gemini_only(self):
 
             model = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.EXTENDED_REASONING)
             # Gemini should return one of its models for extended reasoning
-            # The default behavior may return flash when pro is not explicitly preferred
-            assert model in ["gemini-3-pro-preview", "gemini-2.5-flash", "gemini-2.0-flash"]
+            # The default behavior prefers pro models with thinking support
+            assert model in ["gemini-3.1-pro-preview", "gemini-2.5-pro", "gemini-3-flash-preview", "gemini-2.5-flash"]
 
     def test_fast_response_with_openai(self):
         """Test FAST_RESPONSE with OpenAI provider."""
@@ -133,8 +133,8 @@ def test_fast_response_with_openai(self):
             ModelProviderRegistry.register_provider(ProviderType.OPENAI, OpenAIModelProvider)
 
             model = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.FAST_RESPONSE)
-            # OpenAI now prefers gpt-5.2 for fast response (based on our new preference order)
-            assert model == "gpt-5.2"
+            # OpenAI now prefers gpt-5.4-mini for fast response (based on new preference order)
+            assert model == "gpt-5.4-mini"
 
     def test_fast_response_with_gemini_only(self):
         """Test FAST_RESPONSE prefers flash when only Gemini is available."""
@@ -151,7 +151,7 @@ def test_fast_response_with_gemini_only(self):
 
             model = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.FAST_RESPONSE)
             # Gemini should return one of its models for fast response
-            assert model in ["gemini-2.5-flash", "gemini-2.0-flash", "gemini-2.5-pro"]
+            assert model in ["gemini-3-flash-preview", "gemini-2.5-flash"]
 
     def test_balanced_category_fallback(self):
         """Test BALANCED category uses existing logic."""
@@ -167,8 +167,8 @@ def test_balanced_category_fallback(self):
             ModelProviderRegistry.register_provider(ProviderType.OPENAI, OpenAIModelProvider)
 
             model = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.BALANCED)
-            # OpenAI prefers gpt-5.2 for balanced (based on our new preference order)
-            assert model == "gpt-5.2"
+            # OpenAI prefers gpt-5.4 for balanced (based on new preference order)
+            assert model == "gpt-5.4"
 
     def test_no_category_uses_balanced_logic(self):
         """Test that no category specified uses balanced logic."""
@@ -179,8 +179,8 @@ def test_no_category_uses_balanced_logic(self):
             ModelProviderRegistry.register_provider(ProviderType.GOOGLE, GeminiModelProvider)
 
             model = ModelProviderRegistry.get_preferred_fallback_model()
-            # Should pick flash for balanced use
-            assert model == "gemini-2.5-flash"
+            # Should pick flash for balanced use (flash preview sorts highest)
+            assert model == "gemini-3-flash-preview"
 
 
 class TestFlexibleModelSelection:
@@ -195,21 +195,21 @@ def test_fallback_handles_mixed_model_names(self):
                 "env": {"OPENAI_API_KEY": "test-key"},
                 "provider_type": ProviderType.OPENAI,
                 "category": ToolModelCategory.EXTENDED_REASONING,
-                "expected": "gpt-5.1-codex",  # GPT-5.1-Codex prioritized for coding tasks
+                "expected": "gpt-5.4-pro",  # GPT-5.4 Pro prioritized for reasoning tasks
             },
             # Case 2: Gemini provider for fast response
             {
                 "env": {"GEMINI_API_KEY": "test-key"},
                 "provider_type": ProviderType.GOOGLE,
                 "category": ToolModelCategory.FAST_RESPONSE,
-                "expected": "gemini-2.5-flash",
+                "expected": "gemini-3-flash-preview",
             },
             # Case 3: OpenAI provider for fast response
             {
                 "env": {"OPENAI_API_KEY": "test-key"},
                 "provider_type": ProviderType.OPENAI,
                 "category": ToolModelCategory.FAST_RESPONSE,
-                "expected": "gpt-5.2",  # Based on new preference order
+                "expected": "gpt-5.4-mini",  # Based on new preference order
             },
         ]
 
diff --git a/tests/test_provider_retry_logic.py b/tests/test_provider_retry_logic.py
index 5c49161b3..2a26b8b12 100644
--- a/tests/test_provider_retry_logic.py
+++ b/tests/test_provider_retry_logic.py
@@ -13,7 +13,7 @@ def _mock_chat_response(content: str = "retry success") -> SimpleNamespace:
     usage = SimpleNamespace(prompt_tokens=10, completion_tokens=5, total_tokens=15)
     message = SimpleNamespace(content=content)
     choice = SimpleNamespace(message=message, finish_reason="stop")
-    return SimpleNamespace(choices=[choice], model="gpt-4.1", id="resp-1", created=123, usage=usage)
+    return SimpleNamespace(choices=[choice], model="gpt-5.4", id="resp-1", created=123, usage=usage)
 
 
 def test_openai_provider_retries_on_transient_error(monkeypatch):
@@ -36,7 +36,7 @@ def create_completion(**kwargs):
         responses=SimpleNamespace(create=lambda **_: None),
     )
 
-    result = provider.generate_content("hello", "gpt-4.1")
+    result = provider.generate_content("hello", "gpt-5.4")
 
     assert attempts["count"] == 2, "Expected a retry before succeeding"
     assert result.content == "second attempt response"
@@ -67,7 +67,7 @@ def create_completion(**kwargs):
     )
 
     with pytest.raises(RuntimeError) as excinfo:
-        provider.generate_content("hello", "gpt-4.1")
+        provider.generate_content("hello", "gpt-5.4")
 
     assert "after 1 attempt" in str(excinfo.value)
     assert attempts["count"] == 1
diff --git a/tests/test_provider_routing_bugs.py b/tests/test_provider_routing_bugs.py
index 4e0c2f165..b0b723554 100644
--- a/tests/test_provider_routing_bugs.py
+++ b/tests/test_provider_routing_bugs.py
@@ -269,7 +269,7 @@ def test_openrouter_alias_restrictions_bug_reproduction(self):
             os.environ.pop("OPENAI_API_KEY", None)
             os.environ.pop("XAI_API_KEY", None)
             os.environ["OPENROUTER_API_KEY"] = "test-key"
-            os.environ["OPENROUTER_ALLOWED_MODELS"] = "o3-mini,pro,gpt4.1,flash,o4-mini,o3"  # User's exact config
+            os.environ["OPENROUTER_ALLOWED_MODELS"] = "o3-mini,pro,gpt5.4,flash,o4-mini,o3"  # User's exact config
 
             # Register OpenRouter provider
             from providers.openrouter import OpenRouterProvider
@@ -281,7 +281,7 @@ def test_openrouter_alias_restrictions_bug_reproduction(self):
 
             # ASSERTION: Should have models available, not 0
             assert len(available_models) > 0, (
-                f"Expected models available with alias restrictions 'o3-mini,pro,gpt4.1,flash,o4-mini,o3', "
+                f"Expected models available with alias restrictions 'o3-mini,pro,gpt5.4,flash,o4-mini,o3', "
                 f"but got {len(available_models)} models. Available: {list(available_models.keys())}"
             )
 
@@ -291,7 +291,7 @@ def test_openrouter_alias_restrictions_bug_reproduction(self):
             # flash -> google/gemini-2.5-flash
             # o4-mini -> openai/o4-mini
             # o3 -> openai/o3
-            # gpt4.1 -> should not exist (expected to be filtered out)
+            # gpt5.4 -> should not exist (expected to be filtered out)
 
             expected_models = {"o3-mini", "pro", "flash", "o4-mini", "o3"}
 
diff --git a/tests/test_supported_models_aliases.py b/tests/test_supported_models_aliases.py
index ee23f16bb..ec18c2dd4 100644
--- a/tests/test_supported_models_aliases.py
+++ b/tests/test_supported_models_aliases.py
@@ -20,22 +20,25 @@ def test_gemini_provider_aliases(self):
 
         # Test specific aliases
         assert "flash" in provider.MODEL_CAPABILITIES["gemini-2.5-flash"].aliases
-        assert "pro" in provider.MODEL_CAPABILITIES["gemini-3-pro-preview"].aliases
-        assert "flash-2.0" in provider.MODEL_CAPABILITIES["gemini-2.0-flash"].aliases
-        assert "flash2" in provider.MODEL_CAPABILITIES["gemini-2.0-flash"].aliases
-        assert "flashlite" in provider.MODEL_CAPABILITIES["gemini-2.0-flash-lite"].aliases
-        assert "flash-lite" in provider.MODEL_CAPABILITIES["gemini-2.0-flash-lite"].aliases
+        assert "pro" in provider.MODEL_CAPABILITIES["gemini-3.1-pro-preview"].aliases
+        assert "flash3" in provider.MODEL_CAPABILITIES["gemini-3-flash-preview"].aliases
+        assert "gemini3-flash" in provider.MODEL_CAPABILITIES["gemini-3-flash-preview"].aliases
+        assert "flashlite" in provider.MODEL_CAPABILITIES["gemini-3.1-flash-lite-preview"].aliases
+        assert "flash-lite" in provider.MODEL_CAPABILITIES["gemini-3.1-flash-lite-preview"].aliases
+        assert "lite" in provider.MODEL_CAPABILITIES["gemini-3.1-flash-lite-preview"].aliases
 
         # Test alias resolution
         assert provider._resolve_model_name("flash") == "gemini-2.5-flash"
-        assert provider._resolve_model_name("pro") == "gemini-3-pro-preview"
-        assert provider._resolve_model_name("flash-2.0") == "gemini-2.0-flash"
-        assert provider._resolve_model_name("flash2") == "gemini-2.0-flash"
-        assert provider._resolve_model_name("flashlite") == "gemini-2.0-flash-lite"
+        assert provider._resolve_model_name("pro") == "gemini-3.1-pro-preview"
+        assert provider._resolve_model_name("flash3") == "gemini-3-flash-preview"
+        assert provider._resolve_model_name("gemini3-flash") == "gemini-3-flash-preview"
+        assert provider._resolve_model_name("flashlite") == "gemini-3.1-flash-lite-preview"
+        assert provider._resolve_model_name("flash-lite") == "gemini-3.1-flash-lite-preview"
+        assert provider._resolve_model_name("lite") == "gemini-3.1-flash-lite-preview"
 
         # Test case insensitive resolution
         assert provider._resolve_model_name("Flash") == "gemini-2.5-flash"
-        assert provider._resolve_model_name("PRO") == "gemini-3-pro-preview"
+        assert provider._resolve_model_name("PRO") == "gemini-3.1-pro-preview"
 
     def test_openai_provider_aliases(self):
         """Test OpenAI provider's alias structure."""
@@ -53,7 +56,9 @@ def test_openai_provider_aliases(self):
         # o4-mini is no longer in its own aliases (removed self-reference)
         assert "o3mini" in provider.MODEL_CAPABILITIES["o3-mini"].aliases
         assert "o3pro" in provider.MODEL_CAPABILITIES["o3-pro"].aliases
-        assert "gpt4.1" in provider.MODEL_CAPABILITIES["gpt-4.1"].aliases
+        assert "gpt5.4" in provider.MODEL_CAPABILITIES["gpt-5.4"].aliases
+        assert "gpt5.4-pro" in provider.MODEL_CAPABILITIES["gpt-5.4-pro"].aliases
+        assert "gpt5.3-codex" in provider.MODEL_CAPABILITIES["gpt-5.3-codex"].aliases
         assert "gpt5.2" in provider.MODEL_CAPABILITIES["gpt-5.2"].aliases
         assert "gpt5.1-codex" in provider.MODEL_CAPABILITIES["gpt-5.1-codex"].aliases
         assert "codex-mini" in provider.MODEL_CAPABILITIES["gpt-5.1-codex-mini"].aliases
@@ -63,7 +68,9 @@ def test_openai_provider_aliases(self):
         assert provider._resolve_model_name("o3mini") == "o3-mini"
         assert provider._resolve_model_name("o3pro") == "o3-pro"  # o3pro resolves to o3-pro
         assert provider._resolve_model_name("o4mini") == "o4-mini"
-        assert provider._resolve_model_name("gpt4.1") == "gpt-4.1"  # gpt4.1 resolves to gpt-4.1
+        assert provider._resolve_model_name("gpt5.4") == "gpt-5.4"  # gpt5.4 resolves to gpt-5.4
+        assert provider._resolve_model_name("gpt5.4-pro") == "gpt-5.4-pro"
+        assert provider._resolve_model_name("gpt5.3-codex") == "gpt-5.3-codex"
         assert provider._resolve_model_name("gpt5.2") == "gpt-5.2"
         assert provider._resolve_model_name("gpt5.1") == "gpt-5.2"
         assert provider._resolve_model_name("gpt5.1-codex") == "gpt-5.1-codex"
@@ -131,7 +138,7 @@ def test_list_models_includes_aliases(self):
         gemini_models = gemini_provider.list_models(respect_restrictions=False)
         assert "gemini-2.5-flash" in gemini_models
         assert "flash" in gemini_models
-        assert "gemini-3-pro-preview" in gemini_models
+        assert "gemini-3.1-pro-preview" in gemini_models
         assert "pro" in gemini_models
 
         # Test OpenAI
@@ -168,7 +175,7 @@ def test_list_models_all_known_variant_includes_aliases(self):
         )
         assert "gemini-2.5-flash" in gemini_all
         assert "flash" in gemini_all
-        assert "gemini-3-pro-preview" in gemini_all
+        assert "gemini-3.1-pro-preview" in gemini_all
         assert "pro" in gemini_all
         # All should be lowercase
         assert all(model == model.lower() for model in gemini_all)
diff --git a/tools/analyze.py b/tools/analyze.py
index 401ca5929..abf302219 100644
--- a/tools/analyze.py
+++ b/tools/analyze.py
@@ -17,7 +17,7 @@
 """
 
 import logging
-from typing import TYPE_CHECKING, Any, Literal, Optional
+from typing import TYPE_CHECKING, Any, Literal
 
 from pydantic import Field, model_validator
 
@@ -108,14 +108,14 @@ class AnalyzeWorkflowRequest(WorkflowRequest):
     )
 
     # Optional images for visual context
-    images: Optional[list[str]] = Field(default=None, description=ANALYZE_WORKFLOW_FIELD_DESCRIPTIONS["images"])
+    images: list[str] | None = Field(default=None, description=ANALYZE_WORKFLOW_FIELD_DESCRIPTIONS["images"])
 
     # Analyze-specific fields (only used in step 1 to initialize)
     # Note: Use relevant_files field instead of files for consistency across workflow tools
-    analysis_type: Optional[Literal["architecture", "performance", "security", "quality", "general"]] = Field(
+    analysis_type: Literal["architecture", "performance", "security", "quality", "general"] | None = Field(
         "general", description=ANALYZE_WORKFLOW_FIELD_DESCRIPTIONS["analysis_type"]
     )
-    output_format: Optional[Literal["summary", "detailed", "actionable"]] = Field(
+    output_format: Literal["summary", "detailed", "actionable"] | None = Field(
         "detailed", description=ANALYZE_WORKFLOW_FIELD_DESCRIPTIONS["output_format"]
     )
 
diff --git a/tools/challenge.py b/tools/challenge.py
index a63463d57..00ce5d53e 100644
--- a/tools/challenge.py
+++ b/tools/challenge.py
@@ -8,7 +8,7 @@
 This is a simple, self-contained tool that doesn't require AI model access.
 """
 
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 from pydantic import Field
 
@@ -180,7 +180,7 @@ async def prepare_prompt(self, request: ChallengeRequest) -> str:
         """Not used since challenge doesn't call AI models"""
         return ""
 
-    def format_response(self, response: str, request: ChallengeRequest, model_info: Optional[dict] = None) -> str:
+    def format_response(self, response: str, request: ChallengeRequest, model_info: dict | None = None) -> str:
         """Not used since challenge doesn't call AI models"""
         return response
 
diff --git a/tools/chat.py b/tools/chat.py
index 8bc7e0ce6..bd050e8c5 100644
--- a/tools/chat.py
+++ b/tools/chat.py
@@ -43,11 +43,11 @@ class ChatRequest(ToolRequest):
     """Request model for Chat tool"""
 
     prompt: str = Field(..., description=CHAT_FIELD_DESCRIPTIONS["prompt"])
-    absolute_file_paths: Optional[list[str]] = Field(
+    absolute_file_paths: list[str] | None = Field(
         default_factory=list,
         description=CHAT_FIELD_DESCRIPTIONS["absolute_file_paths"],
     )
-    images: Optional[list[str]] = Field(default_factory=list, description=CHAT_FIELD_DESCRIPTIONS["images"])
+    images: list[str] | None = Field(default_factory=list, description=CHAT_FIELD_DESCRIPTIONS["images"])
     working_directory_absolute_path: str = Field(
         ...,
         description=CHAT_FIELD_DESCRIPTIONS["working_directory_absolute_path"],
@@ -67,7 +67,7 @@ class ChatTool(SimpleTool):
 
     def __init__(self) -> None:
         super().__init__()
-        self._last_recordable_response: Optional[str] = None
+        self._last_recordable_response: str | None = None
 
     def get_name(self) -> str:
         return "chat"
@@ -78,7 +78,7 @@ def get_description(self) -> str:
             "getting second opinions, and exploring ideas. Use for ideas, validations, questions, and thoughtful explanations."
         )
 
-    def get_annotations(self) -> Optional[dict[str, Any]]:
+    def get_annotations(self) -> dict[str, Any] | None:
         """Chat writes generated artifacts when code-generation is enabled."""
 
         return {"readOnlyHint": False}
@@ -198,7 +198,7 @@ async def prepare_prompt(self, request: ChatRequest) -> str:
         # Use SimpleTool's Chat-style prompt preparation
         return self.prepare_chat_style_prompt(request)
 
-    def _validate_file_paths(self, request) -> Optional[str]:
+    def _validate_file_paths(self, request) -> str | None:
         """Extend validation to cover the working directory path."""
 
         files = self.get_request_files(request)
@@ -233,13 +233,13 @@ def _validate_file_paths(self, request) -> Optional[str]:
                 )
         return None
 
-    def format_response(self, response: str, request: ChatRequest, model_info: Optional[dict] = None) -> str:
+    def format_response(self, response: str, request: ChatRequest, model_info: dict | None = None) -> str:
         """
         Format the chat response to match the original Chat tool exactly.
         """
         self._last_recordable_response = None
         body = response
-        recordable_override: Optional[str] = None
+        recordable_override: str | None = None
 
         if self._model_supports_code_generation():
             block, remainder, _ = self._extract_generated_code_block(response)
@@ -298,7 +298,7 @@ def format_response(self, response: str, request: ChatRequest, model_info: Optio
         return final_output
 
     def _record_assistant_turn(
-        self, continuation_id: str, response_text: str, request, model_info: Optional[dict]
+        self, continuation_id: str, response_text: str, request, model_info: dict | None
     ) -> None:
         recordable = self._last_recordable_response if self._last_recordable_response is not None else response_text
         try:
@@ -318,7 +318,7 @@ def _model_supports_code_generation(self) -> bool:
 
         return bool(capabilities.allow_code_generation)
 
-    def _extract_generated_code_block(self, text: str) -> tuple[Optional[str], str, int]:
+    def _extract_generated_code_block(self, text: str) -> tuple[str | None, str, int]:
         matches = list(re.finditer(r"<GENERATED-CODE>.*?</GENERATED-CODE>", text, flags=re.DOTALL | re.IGNORECASE))
         if not matches:
             return None, text, 0
diff --git a/tools/clink.py b/tools/clink.py
index f984c8c6a..d760cf458 100644
--- a/tools/clink.py
+++ b/tools/clink.py
@@ -4,7 +4,7 @@
 
 import logging
 import re
-from datetime import datetime, timezone
+from datetime import UTC, datetime
 from pathlib import Path
 from typing import Any
 
@@ -455,7 +455,7 @@ def _format_file_references(self, files: list[str]) -> str:
             try:
                 path = Path(file_path)
                 stat = path.stat()
-                modified = datetime.fromtimestamp(stat.st_mtime, tz=timezone.utc).isoformat()
+                modified = datetime.fromtimestamp(stat.st_mtime, tz=UTC).isoformat()
                 size = stat.st_size
                 references.append(f"- {file_path} (last modified {modified}, {size} bytes)")
             except OSError:
diff --git a/tools/codereview.py b/tools/codereview.py
index 921765ec0..3748c34f8 100644
--- a/tools/codereview.py
+++ b/tools/codereview.py
@@ -17,7 +17,7 @@
 """
 
 import logging
-from typing import TYPE_CHECKING, Any, Literal, Optional
+from typing import TYPE_CHECKING, Any, Literal
 
 from pydantic import Field, model_validator
 
@@ -85,27 +85,27 @@ class CodeReviewRequest(WorkflowRequest):
         default_factory=list, description=CODEREVIEW_WORKFLOW_FIELD_DESCRIPTIONS["issues_found"]
     )
     # Deprecated confidence field kept for backward compatibility only
-    confidence: Optional[str] = Field("low", exclude=True)
-    review_validation_type: Optional[Literal["external", "internal"]] = Field(
+    confidence: str | None = Field("low", exclude=True)
+    review_validation_type: Literal["external", "internal"] | None = Field(
         "external", description=CODEREVIEW_WORKFLOW_FIELD_DESCRIPTIONS.get("review_validation_type", "")
     )
 
     # Optional images for visual context
-    images: Optional[list[str]] = Field(default=None, description=CODEREVIEW_WORKFLOW_FIELD_DESCRIPTIONS["images"])
+    images: list[str] | None = Field(default=None, description=CODEREVIEW_WORKFLOW_FIELD_DESCRIPTIONS["images"])
 
     # Code review-specific fields (only used in step 1 to initialize)
-    review_type: Optional[Literal["full", "security", "performance", "quick"]] = Field(
+    review_type: Literal["full", "security", "performance", "quick"] | None = Field(
         "full", description=CODEREVIEW_WORKFLOW_FIELD_DESCRIPTIONS["review_type"]
     )
-    focus_on: Optional[str] = Field(None, description=CODEREVIEW_WORKFLOW_FIELD_DESCRIPTIONS["focus_on"])
-    standards: Optional[str] = Field(None, description=CODEREVIEW_WORKFLOW_FIELD_DESCRIPTIONS["standards"])
-    severity_filter: Optional[Literal["critical", "high", "medium", "low", "all"]] = Field(
+    focus_on: str | None = Field(None, description=CODEREVIEW_WORKFLOW_FIELD_DESCRIPTIONS["focus_on"])
+    standards: str | None = Field(None, description=CODEREVIEW_WORKFLOW_FIELD_DESCRIPTIONS["standards"])
+    severity_filter: Literal["critical", "high", "medium", "low", "all"] | None = Field(
         "all", description=CODEREVIEW_WORKFLOW_FIELD_DESCRIPTIONS["severity_filter"]
     )
 
     # Override inherited fields to exclude them from schema (except model which needs to be available)
-    temperature: Optional[float] = Field(default=None, exclude=True)
-    thinking_mode: Optional[str] = Field(default=None, exclude=True)
+    temperature: float | None = Field(default=None, exclude=True)
+    thinking_mode: str | None = Field(default=None, exclude=True)
 
     @model_validator(mode="after")
     def validate_step_one_requirements(self):
diff --git a/tools/debug.py b/tools/debug.py
index e8a64290c..5bc3d69d4 100644
--- a/tools/debug.py
+++ b/tools/debug.py
@@ -16,7 +16,7 @@
 """
 
 import logging
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 from pydantic import Field
 
@@ -89,15 +89,15 @@ class DebugInvestigationRequest(WorkflowRequest):
     relevant_context: list[str] = Field(
         default_factory=list, description=DEBUG_INVESTIGATION_FIELD_DESCRIPTIONS["relevant_context"]
     )
-    hypothesis: Optional[str] = Field(None, description=DEBUG_INVESTIGATION_FIELD_DESCRIPTIONS["hypothesis"])
-    confidence: Optional[str] = Field("low", description=DEBUG_INVESTIGATION_FIELD_DESCRIPTIONS["confidence"])
+    hypothesis: str | None = Field(None, description=DEBUG_INVESTIGATION_FIELD_DESCRIPTIONS["hypothesis"])
+    confidence: str | None = Field("low", description=DEBUG_INVESTIGATION_FIELD_DESCRIPTIONS["confidence"])
 
     # Optional images for visual debugging
-    images: Optional[list[str]] = Field(default=None, description=DEBUG_INVESTIGATION_FIELD_DESCRIPTIONS["images"])
+    images: list[str] | None = Field(default=None, description=DEBUG_INVESTIGATION_FIELD_DESCRIPTIONS["images"])
 
     # Override inherited fields to exclude them from schema (except model which needs to be available)
-    temperature: Optional[float] = Field(default=None, exclude=True)
-    thinking_mode: Optional[str] = Field(default=None, exclude=True)
+    temperature: float | None = Field(default=None, exclude=True)
+    thinking_mode: str | None = Field(default=None, exclude=True)
 
 
 class DebugIssueTool(WorkflowTool):
@@ -341,7 +341,7 @@ def _build_investigation_summary(self, consolidated_findings) -> str:
 
         return "\n".join(summary_parts)
 
-    def _extract_error_context(self, consolidated_findings) -> Optional[str]:
+    def _extract_error_context(self, consolidated_findings) -> str | None:
         """Extract error context from investigation findings."""
         error_patterns = ["error", "exception", "stack trace", "traceback", "failure"]
         error_context_parts = []
diff --git a/tools/docgen.py b/tools/docgen.py
index db238e654..85bc52cd2 100644
--- a/tools/docgen.py
+++ b/tools/docgen.py
@@ -19,7 +19,7 @@
 """
 
 import logging
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 from pydantic import Field
 
@@ -74,10 +74,10 @@ class DocgenRequest(WorkflowRequest):
     total_files_to_document: int = Field(0, description=DOCGEN_FIELD_DESCRIPTIONS["total_files_to_document"])
 
     # Documentation generation configuration parameters
-    document_complexity: Optional[bool] = Field(True, description=DOCGEN_FIELD_DESCRIPTIONS["document_complexity"])
-    document_flow: Optional[bool] = Field(True, description=DOCGEN_FIELD_DESCRIPTIONS["document_flow"])
-    update_existing: Optional[bool] = Field(True, description=DOCGEN_FIELD_DESCRIPTIONS["update_existing"])
-    comments_on_complex_logic: Optional[bool] = Field(
+    document_complexity: bool | None = Field(True, description=DOCGEN_FIELD_DESCRIPTIONS["document_complexity"])
+    document_flow: bool | None = Field(True, description=DOCGEN_FIELD_DESCRIPTIONS["document_flow"])
+    update_existing: bool | None = Field(True, description=DOCGEN_FIELD_DESCRIPTIONS["update_existing"])
+    comments_on_complex_logic: bool | None = Field(
         True, description=DOCGEN_FIELD_DESCRIPTIONS["comments_on_complex_logic"]
     )
 
diff --git a/tools/listmodels.py b/tools/listmodels.py
index 120afc189..d6e83ff59 100644
--- a/tools/listmodels.py
+++ b/tools/listmodels.py
@@ -7,7 +7,7 @@
 """
 
 import logging
-from typing import Any, Optional
+from typing import Any
 
 from mcp.types import TextContent
 
@@ -47,7 +47,7 @@ def get_input_schema(self) -> dict[str, Any]:
             "additionalProperties": False,
         }
 
-    def get_annotations(self) -> Optional[dict[str, Any]]:
+    def get_annotations(self) -> dict[str, Any] | None:
         """Return tool annotations indicating this is a read-only tool"""
         return {"readOnlyHint": True}
 
@@ -66,7 +66,7 @@ async def prepare_prompt(self, request: ToolRequest) -> str:
         """Not used for this utility tool"""
         return ""
 
-    def format_response(self, response: str, request: ToolRequest, model_info: Optional[dict] = None) -> str:
+    def format_response(self, response: str, request: ToolRequest, model_info: dict | None = None) -> str:
         """Not used for this utility tool"""
         return response
 
@@ -267,7 +267,7 @@ def _format_context(tokens: int) -> str:
                             output_lines.append("- *No models allowed by current restriction policy.*")
                     else:
                         available_models = provider.list_models(respect_restrictions=True)
-                        providers_models: dict[str, list[tuple[int, str, Optional[Any]]]] = {}
+                        providers_models: dict[str, list[tuple[int, str, Any | None]]] = {}
 
                         for model_name in available_models:
                             config = registry.resolve(model_name)
diff --git a/tools/models.py b/tools/models.py
index 7b431d532..32c8aca52 100644
--- a/tools/models.py
+++ b/tools/models.py
@@ -3,7 +3,7 @@
 """
 
 from enum import Enum
-from typing import Any, Literal, Optional
+from typing import Any, Literal
 
 from pydantic import BaseModel, Field
 
@@ -44,10 +44,10 @@ class ToolOutput(BaseModel):
         "continuation_available",
         "no_bug_found",
     ] = "success"
-    content: Optional[str] = Field(None, description="The main content/response from the tool")
+    content: str | None = Field(None, description="The main content/response from the tool")
     content_type: Literal["text", "markdown", "json"] = "text"
-    metadata: Optional[dict[str, Any]] = Field(default_factory=dict)
-    continuation_offer: Optional[ContinuationOffer] = Field(
+    metadata: dict[str, Any] | None = Field(default_factory=dict)
+    continuation_offer: ContinuationOffer | None = Field(
         None, description="Optional offer for Agent to continue conversation"
     )
 
@@ -57,10 +57,10 @@ class FilesNeededRequest(BaseModel):
 
     status: Literal["files_required_to_continue"] = "files_required_to_continue"
     mandatory_instructions: str = Field(..., description="Critical instructions for Agent regarding required context")
-    files_needed: Optional[list[str]] = Field(
+    files_needed: list[str] | None = Field(
         default_factory=list, description="Specific files that are needed for analysis"
     )
-    suggested_next_action: Optional[dict[str, Any]] = Field(
+    suggested_next_action: dict[str, Any] | None = Field(
         None,
         description="Suggested tool call with parameters after getting clarification",
     )
@@ -70,8 +70,8 @@ class FullCodereviewRequired(BaseModel):
     """Request for full code review when scope is too large for quick review"""
 
     status: Literal["full_codereview_required"] = "full_codereview_required"
-    important: Optional[str] = Field(None, description="Important message about escalation")
-    reason: Optional[str] = Field(None, description="Reason why full review is needed")
+    important: str | None = Field(None, description="Important message about escalation")
+    reason: str | None = Field(None, description="Reason why full review is needed")
 
 
 class FocusedReviewRequired(BaseModel):
@@ -116,7 +116,7 @@ class RefactorOpportunity(BaseModel):
     rationale: str = Field(..., description="Why this improves the code")
     code_to_replace: str = Field(..., description="Original code that should be changed")
     replacement_code_snippet: str = Field(..., description="Refactored version of the code")
-    new_code_snippets: Optional[list[dict]] = Field(
+    new_code_snippets: list[dict] | None = Field(
         default_factory=list, description="Additional code snippets to be added"
     )
 
@@ -166,7 +166,7 @@ class TraceEntryPoint(BaseModel):
     class_or_struct: str = Field(..., description="Class or module name")
     method: str = Field(..., description="Method or function name")
     signature: str = Field(..., description="Full method signature")
-    parameters: Optional[dict[str, Any]] = Field(default_factory=dict, description="Parameter values used in analysis")
+    parameters: dict[str, Any] | None = Field(default_factory=dict, description="Parameter values used in analysis")
 
 
 class TraceTarget(BaseModel):
@@ -184,7 +184,7 @@ class CallPathStep(BaseModel):
     from_info: dict[str, Any] = Field(..., description="Source location information", alias="from")
     to: dict[str, Any] = Field(..., description="Target location information")
     reason: str = Field(..., description="Reason for the call or dependency")
-    condition: Optional[str] = Field(None, description="Conditional logic if applicable")
+    condition: str | None = Field(None, description="Conditional logic if applicable")
     ambiguous: bool = Field(False, description="Whether this call is ambiguous")
 
 
@@ -262,24 +262,22 @@ class TraceComplete(BaseModel):
     trace_type: Literal["precision", "dependencies"] = Field(..., description="Type of trace performed")
 
     # Precision mode fields
-    entry_point: Optional[TraceEntryPoint] = Field(None, description="Entry point for precision trace")
-    call_path: Optional[list[CallPathStep]] = Field(default_factory=list, description="Call path for precision trace")
-    branching_points: Optional[list[BranchingPoint]] = Field(default_factory=list, description="Branching points")
-    side_effects: Optional[list[SideEffect]] = Field(default_factory=list, description="Side effects detected")
-    unresolved: Optional[list[UnresolvedDependency]] = Field(
-        default_factory=list, description="Unresolved dependencies"
-    )
+    entry_point: TraceEntryPoint | None = Field(None, description="Entry point for precision trace")
+    call_path: list[CallPathStep] | None = Field(default_factory=list, description="Call path for precision trace")
+    branching_points: list[BranchingPoint] | None = Field(default_factory=list, description="Branching points")
+    side_effects: list[SideEffect] | None = Field(default_factory=list, description="Side effects detected")
+    unresolved: list[UnresolvedDependency] | None = Field(default_factory=list, description="Unresolved dependencies")
 
     # Dependencies mode fields
-    target: Optional[TraceTarget] = Field(None, description="Target for dependency analysis")
-    incoming_dependencies: Optional[list[IncomingDependency]] = Field(
+    target: TraceTarget | None = Field(None, description="Target for dependency analysis")
+    incoming_dependencies: list[IncomingDependency] | None = Field(
         default_factory=list, description="Incoming dependencies"
     )
-    outgoing_dependencies: Optional[list[OutgoingDependency]] = Field(
+    outgoing_dependencies: list[OutgoingDependency] | None = Field(
         default_factory=list, description="Outgoing dependencies"
     )
-    type_dependencies: Optional[list[TypeDependency]] = Field(default_factory=list, description="Type dependencies")
-    state_access: Optional[list[StateAccess]] = Field(default_factory=list, description="State access information")
+    type_dependencies: list[TypeDependency] | None = Field(default_factory=list, description="Type dependencies")
+    state_access: list[StateAccess] | None = Field(default_factory=list, description="State access information")
 
 
 class DiagnosticHypothesis(BaseModel):
@@ -301,7 +299,7 @@ class StructuredDebugResponse(BaseModel):
         default_factory=list,
         description="Immediate steps to take regardless of root cause",
     )
-    additional_context_needed: Optional[list[str]] = Field(
+    additional_context_needed: list[str] | None = Field(
         default_factory=list,
         description="Additional files or information that would help with analysis",
     )
@@ -332,7 +330,7 @@ class DebugAnalysisComplete(BaseModel):
     key_findings: list[str] = Field(..., description="Important discoveries made during analysis")
     immediate_actions: list[str] = Field(..., description="Steps to take regardless of which hypothesis is correct")
     recommended_tools: list[str] = Field(default_factory=list, description="Additional tools recommended for analysis")
-    prevention_strategy: Optional[str] = Field(
+    prevention_strategy: str | None = Field(
         None, description="Targeted measures to prevent this exact issue from recurring"
     )
     investigation_summary: str = Field(
diff --git a/tools/precommit.py b/tools/precommit.py
index 29a2bd235..5dfac8ac2 100644
--- a/tools/precommit.py
+++ b/tools/precommit.py
@@ -16,7 +16,7 @@
 """
 
 import logging
-from typing import TYPE_CHECKING, Any, Literal, Optional
+from typing import TYPE_CHECKING, Any, Literal
 
 from pydantic import Field, model_validator
 
@@ -84,29 +84,27 @@ class PrecommitRequest(WorkflowRequest):
     issues_found: list[dict] = Field(
         default_factory=list, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["issues_found"]
     )
-    precommit_type: Optional[Literal["external", "internal"]] = Field(
+    precommit_type: Literal["external", "internal"] | None = Field(
         "external", description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["precommit_type"]
     )
 
     # Optional images for visual validation
-    images: Optional[list[str]] = Field(default=None, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["images"])
+    images: list[str] | None = Field(default=None, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["images"])
 
     # Precommit-specific fields (only used in step 1 to initialize)
     # Required for step 1, validated in model_validator
-    path: Optional[str] = Field(None, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["path"])
-    compare_to: Optional[str] = Field(None, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["compare_to"])
-    include_staged: Optional[bool] = Field(True, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["include_staged"])
-    include_unstaged: Optional[bool] = Field(
-        True, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["include_unstaged"]
-    )
-    focus_on: Optional[str] = Field(None, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["focus_on"])
-    severity_filter: Optional[Literal["critical", "high", "medium", "low", "all"]] = Field(
+    path: str | None = Field(None, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["path"])
+    compare_to: str | None = Field(None, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["compare_to"])
+    include_staged: bool | None = Field(True, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["include_staged"])
+    include_unstaged: bool | None = Field(True, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["include_unstaged"])
+    focus_on: str | None = Field(None, description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["focus_on"])
+    severity_filter: Literal["critical", "high", "medium", "low", "all"] | None = Field(
         "all", description=PRECOMMIT_WORKFLOW_FIELD_DESCRIPTIONS["severity_filter"]
     )
 
     # Override inherited fields to exclude them from schema (except model which needs to be available)
-    temperature: Optional[float] = Field(default=None, exclude=True)
-    thinking_mode: Optional[str] = Field(default=None, exclude=True)
+    temperature: float | None = Field(default=None, exclude=True)
+    thinking_mode: str | None = Field(default=None, exclude=True)
 
     @model_validator(mode="after")
     def validate_step_one_requirements(self):
diff --git a/tools/refactor.py b/tools/refactor.py
index 715914328..f0df348cc 100644
--- a/tools/refactor.py
+++ b/tools/refactor.py
@@ -17,7 +17,7 @@
 """
 
 import logging
-from typing import TYPE_CHECKING, Any, Literal, Optional
+from typing import TYPE_CHECKING, Any, Literal
 
 from pydantic import Field, model_validator
 
@@ -108,25 +108,25 @@ class RefactorRequest(WorkflowRequest):
         default_factory=list, description=REFACTOR_FIELD_DESCRIPTIONS["relevant_context"]
     )
     issues_found: list[dict] = Field(default_factory=list, description=REFACTOR_FIELD_DESCRIPTIONS["issues_found"])
-    confidence: Optional[Literal["exploring", "incomplete", "partial", "complete"]] = Field(
+    confidence: Literal["exploring", "incomplete", "partial", "complete"] | None = Field(
         "incomplete", description=REFACTOR_FIELD_DESCRIPTIONS["confidence"]
     )
 
     # Optional images for visual context
-    images: Optional[list[str]] = Field(default=None, description=REFACTOR_FIELD_DESCRIPTIONS["images"])
+    images: list[str] | None = Field(default=None, description=REFACTOR_FIELD_DESCRIPTIONS["images"])
 
     # Refactor-specific fields (only used in step 1 to initialize)
-    refactor_type: Optional[Literal["codesmells", "decompose", "modernize", "organization"]] = Field(
+    refactor_type: Literal["codesmells", "decompose", "modernize", "organization"] | None = Field(
         "codesmells", description=REFACTOR_FIELD_DESCRIPTIONS["refactor_type"]
     )
-    focus_areas: Optional[list[str]] = Field(None, description=REFACTOR_FIELD_DESCRIPTIONS["focus_areas"])
-    style_guide_examples: Optional[list[str]] = Field(
+    focus_areas: list[str] | None = Field(None, description=REFACTOR_FIELD_DESCRIPTIONS["focus_areas"])
+    style_guide_examples: list[str] | None = Field(
         None, description=REFACTOR_FIELD_DESCRIPTIONS["style_guide_examples"]
     )
 
     # Override inherited fields to exclude them from schema (except model which needs to be available)
-    temperature: Optional[float] = Field(default=None, exclude=True)
-    thinking_mode: Optional[str] = Field(default=None, exclude=True)
+    temperature: float | None = Field(default=None, exclude=True)
+    thinking_mode: str | None = Field(default=None, exclude=True)
 
     @model_validator(mode="after")
     def validate_step_one_requirements(self):
diff --git a/tools/secaudit.py b/tools/secaudit.py
index 56415c804..c52e106cc 100644
--- a/tools/secaudit.py
+++ b/tools/secaudit.py
@@ -18,7 +18,7 @@
 """
 
 import logging
-from typing import TYPE_CHECKING, Any, Literal, Optional
+from typing import TYPE_CHECKING, Any, Literal
 
 from pydantic import Field, model_validator
 
@@ -79,23 +79,23 @@ class SecauditRequest(WorkflowRequest):
     issues_found: list[dict] = Field(
         default_factory=list, description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["issues_found"]
     )
-    confidence: Optional[str] = Field("low", description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["confidence"])
+    confidence: str | None = Field("low", description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["confidence"])
 
     # Optional images for visual context
-    images: Optional[list[str]] = Field(default=None, description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["images"])
+    images: list[str] | None = Field(default=None, description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["images"])
 
     # Security audit-specific fields
-    security_scope: Optional[str] = Field(None, description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["security_scope"])
-    threat_level: Optional[Literal["low", "medium", "high", "critical"]] = Field(
+    security_scope: str | None = Field(None, description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["security_scope"])
+    threat_level: Literal["low", "medium", "high", "critical"] | None = Field(
         "medium", description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["threat_level"]
     )
-    compliance_requirements: Optional[list[str]] = Field(
+    compliance_requirements: list[str] | None = Field(
         default_factory=list, description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["compliance_requirements"]
     )
-    audit_focus: Optional[Literal["owasp", "compliance", "infrastructure", "dependencies", "comprehensive"]] = Field(
+    audit_focus: Literal["owasp", "compliance", "infrastructure", "dependencies", "comprehensive"] | None = Field(
         "comprehensive", description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["audit_focus"]
     )
-    severity_filter: Optional[Literal["critical", "high", "medium", "low", "all"]] = Field(
+    severity_filter: Literal["critical", "high", "medium", "low", "all"] | None = Field(
         "all", description=SECAUDIT_WORKFLOW_FIELD_DESCRIPTIONS["severity_filter"]
     )
 
diff --git a/tools/shared/base_models.py b/tools/shared/base_models.py
index 050670143..92eeda697 100644
--- a/tools/shared/base_models.py
+++ b/tools/shared/base_models.py
@@ -11,7 +11,6 @@
 """
 
 import logging
-from typing import Optional
 
 from pydantic import BaseModel, Field, field_validator
 
@@ -67,15 +66,15 @@ class ToolRequest(BaseModel):
     """
 
     # Model configuration
-    model: Optional[str] = Field(None, description=COMMON_FIELD_DESCRIPTIONS["model"])
-    temperature: Optional[float] = Field(None, ge=0.0, le=1.0, description=COMMON_FIELD_DESCRIPTIONS["temperature"])
-    thinking_mode: Optional[str] = Field(None, description=COMMON_FIELD_DESCRIPTIONS["thinking_mode"])
+    model: str | None = Field(None, description=COMMON_FIELD_DESCRIPTIONS["model"])
+    temperature: float | None = Field(None, ge=0.0, le=1.0, description=COMMON_FIELD_DESCRIPTIONS["temperature"])
+    thinking_mode: str | None = Field(None, description=COMMON_FIELD_DESCRIPTIONS["thinking_mode"])
 
     # Conversation support
-    continuation_id: Optional[str] = Field(None, description=COMMON_FIELD_DESCRIPTIONS["continuation_id"])
+    continuation_id: str | None = Field(None, description=COMMON_FIELD_DESCRIPTIONS["continuation_id"])
 
     # Visual context
-    images: Optional[list[str]] = Field(None, description=COMMON_FIELD_DESCRIPTIONS["images"])
+    images: list[str] | None = Field(None, description=COMMON_FIELD_DESCRIPTIONS["images"])
 
 
 class BaseWorkflowRequest(ToolRequest):
@@ -120,8 +119,8 @@ class WorkflowRequest(BaseWorkflowRequest):
     confidence: str = Field("low", description=WORKFLOW_FIELD_DESCRIPTIONS["confidence"])
 
     # Optional workflow fields
-    hypothesis: Optional[str] = Field(None, description=WORKFLOW_FIELD_DESCRIPTIONS["hypothesis"])
-    use_assistant_model: Optional[bool] = Field(True, description=WORKFLOW_FIELD_DESCRIPTIONS["use_assistant_model"])
+    hypothesis: str | None = Field(None, description=WORKFLOW_FIELD_DESCRIPTIONS["hypothesis"])
+    use_assistant_model: bool | None = Field(True, description=WORKFLOW_FIELD_DESCRIPTIONS["use_assistant_model"])
 
     @field_validator("files_checked", "relevant_files", "relevant_context", mode="before")
     @classmethod
diff --git a/tools/shared/base_tool.py b/tools/shared/base_tool.py
index 94506e838..f32f6e267 100644
--- a/tools/shared/base_tool.py
+++ b/tools/shared/base_tool.py
@@ -202,7 +202,7 @@ def _augment_system_prompt_with_capabilities(
         suffix = "" if base_prompt.endswith("\n\n") else "\n\n"
         return f"{base_prompt}{suffix}{addition_text}"
 
-    def get_annotations(self) -> Optional[dict[str, Any]]:
+    def get_annotations(self) -> dict[str, Any] | None:
         """
         Return optional annotations for this tool.
 
@@ -349,7 +349,7 @@ def _format_available_models_list(self) -> str:
         return display
 
     @staticmethod
-    def _format_context_window(tokens: int) -> Optional[str]:
+    def _format_context_window(tokens: int) -> str | None:
         """Convert a raw context window into a short display string."""
 
         if not tokens or tokens <= 0:
@@ -467,7 +467,7 @@ def _get_ranked_model_summaries(self, limit: int = 5) -> tuple[list[str], int, b
 
         return summaries, len(filtered), bool(allowed_map)
 
-    def _get_restriction_note(self) -> Optional[str]:
+    def _get_restriction_note(self) -> str | None:
         """Return a string describing active per-provider allowlists, if any."""
 
         env_labels = {
@@ -651,7 +651,7 @@ def get_request_model(self):
         """
         pass
 
-    def validate_file_paths(self, request) -> Optional[str]:
+    def validate_file_paths(self, request) -> str | None:
         """
         Validate that all file paths in the request are absolute.
 
@@ -757,7 +757,7 @@ def get_model_provider(self, model_name: str) -> ModelProvider:
 
     # === CONVERSATION AND FILE HANDLING METHODS ===
 
-    def get_conversation_embedded_files(self, continuation_id: Optional[str]) -> list[str]:
+    def get_conversation_embedded_files(self, continuation_id: str | None) -> list[str]:
         """
         Get list of files already embedded in conversation history.
 
@@ -785,7 +785,7 @@ def get_conversation_embedded_files(self, continuation_id: Optional[str]) -> lis
         logger.debug(f"[FILES] {self.name}: Found {len(embedded_files)} embedded files")
         return embedded_files
 
-    def filter_new_files(self, requested_files: list[str], continuation_id: Optional[str]) -> list[str]:
+    def filter_new_files(self, requested_files: list[str], continuation_id: str | None) -> list[str]:
         """
         Filter out files that are already embedded in conversation history.
 
@@ -883,7 +883,7 @@ def format_conversation_turn(self, turn: ConversationTurn) -> list[str]:
 
         return parts
 
-    def handle_prompt_file(self, files: Optional[list[str]]) -> tuple[Optional[str], Optional[list[str]]]:
+    def handle_prompt_file(self, files: list[str] | None) -> tuple[str | None, list[str] | None]:
         """
         Check for and handle prompt.txt in the absolute file paths list.
 
@@ -962,7 +962,7 @@ def get_prompt_content_for_size_validation(self, user_content: str) -> str:
         # Default implementation: validate the full user content
         return user_content
 
-    def check_prompt_size(self, text: str) -> Optional[dict[str, Any]]:
+    def check_prompt_size(self, text: str) -> dict[str, Any] | None:
         """
         Check if USER INPUT text is too large for MCP transport boundary.
 
@@ -999,13 +999,13 @@ def check_prompt_size(self, text: str) -> Optional[dict[str, Any]]:
     def _prepare_file_content_for_prompt(
         self,
         request_files: list[str],
-        continuation_id: Optional[str],
+        continuation_id: str | None,
         context_description: str = "New files",
-        max_tokens: Optional[int] = None,
+        max_tokens: int | None = None,
         reserve_tokens: int = 1_000,
-        remaining_budget: Optional[int] = None,
-        arguments: Optional[dict] = None,
-        model_context: Optional[Any] = None,
+        remaining_budget: int | None = None,
+        arguments: dict | None = None,
+        model_context: Any | None = None,
     ) -> tuple[str, list[str]]:
         """
         Centralized file processing implementing dual prioritization strategy.
@@ -1163,7 +1163,7 @@ def _prepare_file_content_for_prompt(
         )
         return result, actually_processed_files
 
-    def get_websearch_instruction(self, tool_specific: Optional[str] = None) -> str:
+    def get_websearch_instruction(self, tool_specific: str | None = None) -> str:
         """
         Generate standardized web search instruction.
 
@@ -1450,8 +1450,8 @@ def validate_and_correct_temperature(self, temperature: float, model_context: An
             return temperature, [f"Temperature validation failed: {e}"]
 
     def _validate_image_limits(
-        self, images: Optional[list[str]], model_context: Optional[Any] = None, continuation_id: Optional[str] = None
-    ) -> Optional[dict]:
+        self, images: list[str] | None, model_context: Any | None = None, continuation_id: str | None = None
+    ) -> dict | None:
         """
         Validate image size and count against model capabilities.
 
@@ -1600,7 +1600,7 @@ def _validate_image_limits(
         logger.debug(f"Image validation passed: {len(images)} images, {total_size_mb:.1f}MB total")
         return None
 
-    def _parse_response(self, raw_text: str, request, model_info: Optional[dict] = None):
+    def _parse_response(self, raw_text: str, request, model_info: dict | None = None):
         """Parse response - will be inherited for now."""
         # Implementation inherited from current base.py
         raise NotImplementedError("Subclasses must implement _parse_response method")
diff --git a/tools/simple/base.py b/tools/simple/base.py
index 2c6ed6b69..6db954ad6 100644
--- a/tools/simple/base.py
+++ b/tools/simple/base.py
@@ -13,7 +13,7 @@
 """
 
 from abc import abstractmethod
-from typing import Any, Optional
+from typing import Any
 
 from tools.shared.base_models import ToolRequest
 from tools.shared.base_tool import BaseTool
@@ -101,7 +101,7 @@ def get_required_fields(self) -> list[str]:
         """
         return []
 
-    def get_annotations(self) -> Optional[dict[str, Any]]:
+    def get_annotations(self) -> dict[str, Any] | None:
         """
         Return tool annotations. Simple tools are read-only by default.
 
@@ -116,7 +116,7 @@ def get_annotations(self) -> Optional[dict[str, Any]]:
         """
         return {"readOnlyHint": True}
 
-    def format_response(self, response: str, request, model_info: Optional[dict] = None) -> str:
+    def format_response(self, response: str, request, model_info: dict | None = None) -> str:
         """
         Format the AI response before returning to the client.
 
@@ -168,7 +168,7 @@ def get_request_model(self):
 
     # Hook methods for safe attribute access without hasattr/getattr
 
-    def get_request_model_name(self, request) -> Optional[str]:
+    def get_request_model_name(self, request) -> str | None:
         """Get model name from request. Override for custom model name handling."""
         try:
             return request.model
@@ -182,7 +182,7 @@ def get_request_images(self, request) -> list:
         except AttributeError:
             return []
 
-    def get_request_continuation_id(self, request) -> Optional[str]:
+    def get_request_continuation_id(self, request) -> str | None:
         """Get continuation_id from request. Override for custom continuation handling."""
         try:
             return request.continuation_id
@@ -196,7 +196,7 @@ def get_request_prompt(self, request) -> str:
         except AttributeError:
             return ""
 
-    def get_request_temperature(self, request) -> Optional[float]:
+    def get_request_temperature(self, request) -> float | None:
         """Get temperature from request. Override for custom temperature handling."""
         try:
             return request.temperature
@@ -222,7 +222,7 @@ def get_validated_temperature(self, request, model_context: Any) -> tuple[float,
             temperature = self.get_default_temperature()
         return self.validate_and_correct_temperature(temperature, model_context)
 
-    def get_request_thinking_mode(self, request) -> Optional[str]:
+    def get_request_thinking_mode(self, request) -> str | None:
         """Get thinking_mode from request. Override for custom thinking mode handling."""
         try:
             return request.thinking_mode
@@ -587,7 +587,7 @@ async def execute(self, arguments: dict[str, Any]) -> list:
             )
             raise ToolExecutionError(error_output.model_dump_json()) from e
 
-    def _parse_response(self, raw_text: str, request, model_info: Optional[dict] = None):
+    def _parse_response(self, raw_text: str, request, model_info: dict | None = None):
         """
         Parse the raw response and format it using the hook method.
 
@@ -634,7 +634,7 @@ def _parse_response(self, raw_text: str, request, model_info: Optional[dict] = N
                 metadata=metadata if metadata else None,
             )
 
-    def _create_continuation_offer(self, request, model_info: Optional[dict] = None):
+    def _create_continuation_offer(self, request, model_info: dict | None = None):
         """Create continuation offer following old base.py pattern"""
         continuation_id = self.get_request_continuation_id(request)
 
@@ -685,7 +685,7 @@ def _create_continuation_offer(self, request, model_info: Optional[dict] = None)
             return None
 
     def _create_continuation_offer_response(
-        self, content: str, continuation_data: dict, request, model_info: Optional[dict] = None
+        self, content: str, continuation_data: dict, request, model_info: dict | None = None
     ):
         """Create response with continuation offer following old base.py pattern"""
         from tools.models import ContinuationOffer, ToolOutput
@@ -735,7 +735,7 @@ def _create_continuation_offer_response(
             return ToolOutput(status="success", content=content, content_type="text")
 
     def _record_assistant_turn(
-        self, continuation_id: str, response_text: str, request, model_info: Optional[dict]
+        self, continuation_id: str, response_text: str, request, model_info: dict | None
     ) -> None:
         """Persist an assistant response in conversation memory."""
 
@@ -855,7 +855,7 @@ def get_prompt_content_for_size_validation(self, user_content: str) -> str:
         # Fallback to default behavior (validate full user content)
         return user_content
 
-    def get_websearch_guidance(self) -> Optional[str]:
+    def get_websearch_guidance(self) -> str | None:
         """
         Return tool-specific web search guidance.
 
@@ -937,7 +937,7 @@ def supports_custom_request_model(self) -> bool:
         """
         return self.get_request_model() != ToolRequest
 
-    def _validate_file_paths(self, request) -> Optional[str]:
+    def _validate_file_paths(self, request) -> str | None:
         """
         Validate that all file paths in the request are absolute paths.
 
diff --git a/tools/testgen.py b/tools/testgen.py
index 705168382..fbbf41fc2 100644
--- a/tools/testgen.py
+++ b/tools/testgen.py
@@ -16,7 +16,7 @@
 """
 
 import logging
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 from pydantic import Field, model_validator
 
@@ -75,14 +75,14 @@ class TestGenRequest(WorkflowRequest):
     relevant_context: list[str] = Field(
         default_factory=list, description=TESTGEN_WORKFLOW_FIELD_DESCRIPTIONS["relevant_context"]
     )
-    confidence: Optional[str] = Field("low", description=TESTGEN_WORKFLOW_FIELD_DESCRIPTIONS["confidence"])
+    confidence: str | None = Field("low", description=TESTGEN_WORKFLOW_FIELD_DESCRIPTIONS["confidence"])
 
     # Optional images for visual context
-    images: Optional[list[str]] = Field(default=None, description=TESTGEN_WORKFLOW_FIELD_DESCRIPTIONS["images"])
+    images: list[str] | None = Field(default=None, description=TESTGEN_WORKFLOW_FIELD_DESCRIPTIONS["images"])
 
     # Override inherited fields to exclude them from schema (except model which needs to be available)
-    temperature: Optional[float] = Field(default=None, exclude=True)
-    thinking_mode: Optional[str] = Field(default=None, exclude=True)
+    temperature: float | None = Field(default=None, exclude=True)
+    thinking_mode: str | None = Field(default=None, exclude=True)
 
     @model_validator(mode="after")
     def validate_step_one_requirements(self):
diff --git a/tools/thinkdeep.py b/tools/thinkdeep.py
index 948375170..cb9a804f4 100644
--- a/tools/thinkdeep.py
+++ b/tools/thinkdeep.py
@@ -14,7 +14,7 @@
 """
 
 import logging
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 from pydantic import Field
 
@@ -56,7 +56,7 @@ class ThinkDeepWorkflowRequest(WorkflowRequest):
         default_factory=list,
         description="Key concepts/methods: 'concept_name' or 'ClassName.methodName'. Focus on core insights, decision points.",
     )
-    hypothesis: Optional[str] = Field(
+    hypothesis: str | None = Field(
         default=None,
         description="Current theory based on evidence. Revise in later steps.",
     )
@@ -73,22 +73,22 @@ class ThinkDeepWorkflowRequest(WorkflowRequest):
 
     # Expert analysis configuration - keep these fields available for configuring the final assistant model
     # in expert analysis (commented out exclude=True)
-    temperature: Optional[float] = Field(
+    temperature: float | None = Field(
         default=None,
         description="Creative thinking temp (0-1, default 0.7)",
         ge=0.0,
         le=1.0,
     )
-    thinking_mode: Optional[str] = Field(
+    thinking_mode: str | None = Field(
         default=None,
         description="Depth: minimal/low/medium/high/max. Default 'high'.",
     )
     # Context files and investigation scope
-    problem_context: Optional[str] = Field(
+    problem_context: str | None = Field(
         default=None,
         description="Additional context about problem/goal. Be expressive.",
     )
-    focus_areas: Optional[list[str]] = Field(
+    focus_areas: list[str] | None = Field(
         default=None,
         description="Focus aspects (architecture, performance, security, etc.)",
     )
@@ -548,7 +548,7 @@ def format_step_response(
         assistant_response: str,
         request,
         status: str = "pause_for_thinkdeep",
-        continuation_id: Optional[str] = None,
+        continuation_id: str | None = None,
         **kwargs,
     ) -> dict:
         """
diff --git a/tools/tracer.py b/tools/tracer.py
index c81cf3942..4560094a0 100644
--- a/tools/tracer.py
+++ b/tools/tracer.py
@@ -20,7 +20,7 @@
 """
 
 import logging
-from typing import TYPE_CHECKING, Any, Literal, Optional
+from typing import TYPE_CHECKING, Any, Literal
 
 from pydantic import Field, field_validator
 
@@ -101,24 +101,22 @@ class TracerRequest(WorkflowRequest):
     relevant_context: list[str] = Field(
         default_factory=list, description=TRACER_WORKFLOW_FIELD_DESCRIPTIONS["relevant_context"]
     )
-    confidence: Optional[str] = Field("exploring", description=TRACER_WORKFLOW_FIELD_DESCRIPTIONS["confidence"])
+    confidence: str | None = Field("exploring", description=TRACER_WORKFLOW_FIELD_DESCRIPTIONS["confidence"])
 
     # Tracer-specific fields (used in step 1 to initialize)
-    trace_mode: Optional[Literal["precision", "dependencies", "ask"]] = Field(
+    trace_mode: Literal["precision", "dependencies", "ask"] | None = Field(
         "ask", description=TRACER_WORKFLOW_FIELD_DESCRIPTIONS["trace_mode"]
     )
-    target_description: Optional[str] = Field(
-        None, description=TRACER_WORKFLOW_FIELD_DESCRIPTIONS["target_description"]
-    )
-    images: Optional[list[str]] = Field(default=None, description=TRACER_WORKFLOW_FIELD_DESCRIPTIONS["images"])
+    target_description: str | None = Field(None, description=TRACER_WORKFLOW_FIELD_DESCRIPTIONS["target_description"])
+    images: list[str] | None = Field(default=None, description=TRACER_WORKFLOW_FIELD_DESCRIPTIONS["images"])
 
     # Exclude fields not relevant to tracing workflow
     issues_found: list[dict] = Field(default_factory=list, exclude=True, description="Tracing doesn't track issues")
-    hypothesis: Optional[str] = Field(default=None, exclude=True, description="Tracing doesn't use hypothesis")
+    hypothesis: str | None = Field(default=None, exclude=True, description="Tracing doesn't use hypothesis")
     # Exclude other non-tracing fields
-    temperature: Optional[float] = Field(default=None, exclude=True)
-    thinking_mode: Optional[str] = Field(default=None, exclude=True)
-    use_assistant_model: Optional[bool] = Field(default=False, exclude=True, description="Tracing is self-contained")
+    temperature: float | None = Field(default=None, exclude=True)
+    thinking_mode: str | None = Field(default=None, exclude=True)
+    use_assistant_model: bool | None = Field(default=False, exclude=True, description="Tracing is self-contained")
 
     @field_validator("step_number")
     @classmethod
diff --git a/tools/version.py b/tools/version.py
index b926491dc..0516fa07c 100644
--- a/tools/version.py
+++ b/tools/version.py
@@ -11,7 +11,7 @@
 import re
 import sys
 from pathlib import Path
-from typing import Any, Optional
+from typing import Any
 
 try:
     from urllib.error import HTTPError, URLError
@@ -79,7 +79,7 @@ def compare_versions(current: str, remote: str) -> int:
         return 0
 
 
-def fetch_github_version() -> Optional[tuple[str, str]]:
+def fetch_github_version() -> tuple[str, str] | None:
     """
     Fetch the latest version information from GitHub repository.
 
@@ -151,7 +151,7 @@ def get_input_schema(self) -> dict[str, Any]:
             "additionalProperties": False,
         }
 
-    def get_annotations(self) -> Optional[dict[str, Any]]:
+    def get_annotations(self) -> dict[str, Any] | None:
         """Return tool annotations indicating this is a read-only tool"""
         return {"readOnlyHint": True}
 
diff --git a/tools/workflow/base.py b/tools/workflow/base.py
index 89287c79e..ffb888096 100644
--- a/tools/workflow/base.py
+++ b/tools/workflow/base.py
@@ -13,7 +13,7 @@
 """
 
 from abc import abstractmethod
-from typing import Any, Optional
+from typing import Any
 
 from tools.shared.base_models import WorkflowRequest
 from tools.shared.base_tool import BaseTool
@@ -110,7 +110,7 @@ def get_required_fields(self) -> list[str]:
         """
         return []
 
-    def get_annotations(self) -> Optional[dict[str, Any]]:
+    def get_annotations(self) -> dict[str, Any] | None:
         """
         Return tool annotations. Workflow tools are read-only by default.
 
@@ -363,7 +363,7 @@ def get_completion_data_key(self) -> str:
         """Get the key name for completion data in the response."""
         return f"complete_{self.get_name()}"
 
-    def get_final_analysis_from_request(self, request) -> Optional[str]:
+    def get_final_analysis_from_request(self, request) -> str | None:
         """Extract final analysis from request. Override for tool-specific extraction."""
         try:
             return request.hypothesis
diff --git a/tools/workflow/workflow_mixin.py b/tools/workflow/workflow_mixin.py
index e929591a7..5d8a6fb0e 100644
--- a/tools/workflow/workflow_mixin.py
+++ b/tools/workflow/workflow_mixin.py
@@ -25,7 +25,7 @@
 import os
 import re
 from abc import ABC, abstractmethod
-from typing import Any, Optional
+from typing import Any
 
 from mcp.types import TextContent
 
@@ -70,7 +70,7 @@ def __init__(self) -> None:
         super().__init__()
         self.work_history: list[dict[str, Any]] = []
         self.consolidated_findings: ConsolidatedFindings = ConsolidatedFindings()
-        self.initial_request: Optional[str] = None
+        self.initial_request: str | None = None
 
     # ================================================================================
     # Abstract Methods - Required Implementation by BaseTool or Subclasses
@@ -115,13 +115,13 @@ def _resolve_model_context(self, arguments: dict[str, Any], request: Any) -> tup
     def _prepare_file_content_for_prompt(
         self,
         request_files: list[str],
-        continuation_id: Optional[str],
+        continuation_id: str | None,
         context_description: str = "New files",
-        max_tokens: Optional[int] = None,
+        max_tokens: int | None = None,
         reserve_tokens: int = 1_000,
-        remaining_budget: Optional[int] = None,
-        arguments: Optional[dict[str, Any]] = None,
-        model_context: Optional[Any] = None,
+        remaining_budget: int | None = None,
+        arguments: dict[str, Any] | None = None,
+        model_context: Any | None = None,
     ) -> tuple[str, list[str]]:
         """Prepare file content for prompts. Usually provided by BaseTool."""
         pass
@@ -479,7 +479,7 @@ def _handle_workflow_file_context(self, request: Any, arguments: dict[str, Any])
             self._reference_workflow_files(request)
 
     def _should_embed_files_in_workflow_step(
-        self, step_number: int, continuation_id: Optional[str], is_final_step: bool
+        self, step_number: int, continuation_id: str | None, is_final_step: bool
     ) -> bool:
         """
         Determine whether to embed file content based on workflow context.
@@ -894,7 +894,7 @@ def get_request_issues_found(self, request: Any) -> list[str]:
         except AttributeError:
             return []
 
-    def get_request_hypothesis(self, request: Any) -> Optional[str]:
+    def get_request_hypothesis(self, request: Any) -> str | None:
         """Get hypothesis from request. Override for custom field mapping."""
         try:
             return request.hypothesis
@@ -945,7 +945,7 @@ def get_request_model_name(self, request: Any) -> str:
         except AttributeError:
             return "flash"
 
-    def get_request_continuation_id(self, request: Any) -> Optional[str]:
+    def get_request_continuation_id(self, request: Any) -> str | None:
         """Get continuation ID from request. Override for custom continuation handling."""
         try:
             return request.continuation_id
diff --git a/utils/client_info.py b/utils/client_info.py
index 707b69a97..e455507c0 100644
--- a/utils/client_info.py
+++ b/utils/client_info.py
@@ -9,12 +9,12 @@
 """
 
 import logging
-from typing import Any, Optional
+from typing import Any
 
 logger = logging.getLogger(__name__)
 
 # Global cache for client information
-_client_info_cache: Optional[dict[str, Any]] = None
+_client_info_cache: dict[str, Any] | None = None
 
 # Mapping of known client names to friendly names
 # This is case-insensitive and checks if the key is contained in the client name
@@ -69,7 +69,7 @@ def get_friendly_name(client_name: str) -> str:
     return DEFAULT_FRIENDLY_NAME
 
 
-def get_cached_client_info() -> Optional[dict[str, Any]]:
+def get_cached_client_info() -> dict[str, Any] | None:
     """
     Get cached client information if available.
 
@@ -80,7 +80,7 @@ def get_cached_client_info() -> Optional[dict[str, Any]]:
     return _client_info_cache
 
 
-def get_client_info_from_context(server: Any) -> Optional[dict[str, Any]]:
+def get_client_info_from_context(server: Any) -> dict[str, Any] | None:
     """
     Extract client information from the MCP server's request context.
 
@@ -192,7 +192,7 @@ def get_client_info_from_context(server: Any) -> Optional[dict[str, Any]]:
         return None
 
 
-def format_client_info(client_info: Optional[dict[str, Any]], use_friendly_name: bool = True) -> str:
+def format_client_info(client_info: dict[str, Any] | None, use_friendly_name: bool = True) -> str:
     """
     Format client information for display.
 
@@ -236,7 +236,7 @@ def get_client_friendly_name() -> str:
     return DEFAULT_FRIENDLY_NAME
 
 
-def log_client_info(server: Any, logger_instance: Optional[logging.Logger] = None) -> None:
+def log_client_info(server: Any, logger_instance: logging.Logger | None = None) -> None:
     """
     Log client information extracted from the server.
 
diff --git a/utils/conversation_memory.py b/utils/conversation_memory.py
index 41a7cd760..25bedb01f 100644
--- a/utils/conversation_memory.py
+++ b/utils/conversation_memory.py
@@ -107,8 +107,8 @@
 import logging
 import os
 import uuid
-from datetime import datetime, timezone
-from typing import Any, Optional
+from datetime import UTC, datetime
+from typing import Any
 
 from pydantic import BaseModel
 
@@ -170,12 +170,12 @@ class ConversationTurn(BaseModel):
     role: str  # "user" or "assistant"
     content: str
     timestamp: str
-    files: Optional[list[str]] = None  # Files referenced in this turn
-    images: Optional[list[str]] = None  # Images referenced in this turn
-    tool_name: Optional[str] = None  # Tool used for this turn
-    model_provider: Optional[str] = None  # Model provider (google, openai, etc)
-    model_name: Optional[str] = None  # Specific model used
-    model_metadata: Optional[dict[str, Any]] = None  # Additional model info
+    files: list[str] | None = None  # Files referenced in this turn
+    images: list[str] | None = None  # Images referenced in this turn
+    tool_name: str | None = None  # Tool used for this turn
+    model_provider: str | None = None  # Model provider (google, openai, etc)
+    model_name: str | None = None  # Specific model used
+    model_metadata: dict[str, Any] | None = None  # Additional model info
 
 
 class ThreadContext(BaseModel):
@@ -197,7 +197,7 @@ class ThreadContext(BaseModel):
     """
 
     thread_id: str
-    parent_thread_id: Optional[str] = None  # Parent thread for conversation chains
+    parent_thread_id: str | None = None  # Parent thread for conversation chains
     created_at: str
     last_updated_at: str
     tool_name: str  # Tool that created this thread (preserved for attribution)
@@ -217,7 +217,7 @@ def get_storage():
     return get_storage_backend()
 
 
-def create_thread(tool_name: str, initial_request: dict[str, Any], parent_thread_id: Optional[str] = None) -> str:
+def create_thread(tool_name: str, initial_request: dict[str, Any], parent_thread_id: str | None = None) -> str:
     """
     Create new conversation thread and return thread ID
 
@@ -240,7 +240,7 @@ def create_thread(tool_name: str, initial_request: dict[str, Any], parent_thread
         - Parent thread creates a chain for conversation history traversal
     """
     thread_id = str(uuid.uuid4())
-    now = datetime.now(timezone.utc).isoformat()
+    now = datetime.now(UTC).isoformat()
 
     # Filter out non-serializable parameters to avoid JSON encoding issues
     filtered_context = {
@@ -269,7 +269,7 @@ def create_thread(tool_name: str, initial_request: dict[str, Any], parent_thread
     return thread_id
 
 
-def get_thread(thread_id: str) -> Optional[ThreadContext]:
+def get_thread(thread_id: str) -> ThreadContext | None:
     """
     Retrieve thread context from in-memory storage
 
@@ -309,12 +309,12 @@ def add_turn(
     thread_id: str,
     role: str,
     content: str,
-    files: Optional[list[str]] = None,
-    images: Optional[list[str]] = None,
-    tool_name: Optional[str] = None,
-    model_provider: Optional[str] = None,
-    model_name: Optional[str] = None,
-    model_metadata: Optional[dict[str, Any]] = None,
+    files: list[str] | None = None,
+    images: list[str] | None = None,
+    tool_name: str | None = None,
+    model_provider: str | None = None,
+    model_name: str | None = None,
+    model_metadata: dict[str, Any] | None = None,
 ) -> bool:
     """
     Add turn to existing thread with atomic file ordering.
@@ -365,7 +365,7 @@ def add_turn(
     turn = ConversationTurn(
         role=role,
         content=content,
-        timestamp=datetime.now(timezone.utc).isoformat(),
+        timestamp=datetime.now(UTC).isoformat(),
         files=files,  # Preserved for cross-tool file context
         images=images,  # Preserved for cross-tool visual context
         tool_name=tool_name,  # Track which tool generated this turn
@@ -375,7 +375,7 @@ def add_turn(
     )
 
     context.turns.append(turn)
-    context.last_updated_at = datetime.now(timezone.utc).isoformat()
+    context.last_updated_at = datetime.now(UTC).isoformat()
 
     # Save back to storage and refresh TTL
     try:
diff --git a/utils/file_utils.py b/utils/file_utils.py
index cc0540886..552d3494b 100644
--- a/utils/file_utils.py
+++ b/utils/file_utils.py
@@ -40,9 +40,8 @@
 import json
 import logging
 import os
-from datetime import datetime, timezone
+from datetime import UTC, datetime
 from pathlib import Path
-from typing import Optional
 
 from .file_types import BINARY_EXTENSIONS, CODE_EXTENSIONS, IMAGE_EXTENSIONS, TEXT_EXTENSIONS
 from .security_config import EXCLUDED_DIRS, is_dangerous_path
@@ -111,7 +110,7 @@ def is_mcp_directory(path: Path) -> bool:
         return False
 
 
-def get_user_home_directory() -> Optional[Path]:
+def get_user_home_directory() -> Path | None:
     """
     Get the user's home directory.
 
@@ -219,7 +218,7 @@ def detect_file_type(file_path: str) -> str:
         return "unknown"
 
 
-def should_add_line_numbers(file_path: str, include_line_numbers: Optional[bool] = None) -> bool:
+def should_add_line_numbers(file_path: str, include_line_numbers: bool | None = None) -> bool:
     """
     Determine if line numbers should be added to a file.
 
@@ -324,7 +323,7 @@ def resolve_and_validate_path(path_str: str) -> Path:
     return resolved_path
 
 
-def expand_paths(paths: list[str], extensions: Optional[set[str]] = None) -> list[str]:
+def expand_paths(paths: list[str], extensions: set[str] | None = None) -> list[str]:
     """
     Expand paths to individual files, handling both files and directories.
 
@@ -419,7 +418,7 @@ def expand_paths(paths: list[str], extensions: Optional[set[str]] = None) -> lis
 
 
 def read_file_content(
-    file_path: str, max_size: int = 1_000_000, *, include_line_numbers: Optional[bool] = None
+    file_path: str, max_size: int = 1_000_000, *, include_line_numbers: bool | None = None
 ) -> tuple[str, int]:
     """
     Read a single file and format it for inclusion in AI prompts.
@@ -469,7 +468,7 @@ def read_file_content(
         logger.debug(f"[FILES] File size for {file_path}: {file_size:,} bytes")
         if file_size > max_size:
             logger.debug(f"[FILES] File too large: {file_path} ({file_size:,} > {max_size:,} bytes)")
-            modified_at = datetime.fromtimestamp(stat_result.st_mtime, tz=timezone.utc).strftime("%Y-%m-%d %H:%M:%S %Z")
+            modified_at = datetime.fromtimestamp(stat_result.st_mtime, tz=UTC).strftime("%Y-%m-%d %H:%M:%S %Z")
             content = (
                 f"\n--- FILE TOO LARGE: {file_path} (Last modified: {modified_at}) ---\n"
                 f"File size: {file_size:,} bytes (max: {max_size:,})\n"
@@ -502,7 +501,7 @@ def read_file_content(
         # NOTE: These markers ("--- BEGIN FILE: ... ---") are distinct from git diff markers
         # ("--- BEGIN DIFF: ... ---") to allow AI to distinguish between complete file content
         # vs. partial diff content when files appear in both sections
-        modified_at = datetime.fromtimestamp(stat_result.st_mtime, tz=timezone.utc).strftime("%Y-%m-%d %H:%M:%S %Z")
+        modified_at = datetime.fromtimestamp(stat_result.st_mtime, tz=UTC).strftime("%Y-%m-%d %H:%M:%S %Z")
         formatted = (
             f"\n--- BEGIN FILE: {file_path} (Last modified: {modified_at}) ---\n"
             f"{file_content}\n"
@@ -522,8 +521,8 @@ def read_file_content(
 
 def read_files(
     file_paths: list[str],
-    code: Optional[str] = None,
-    max_tokens: Optional[int] = None,
+    code: str | None = None,
+    max_tokens: int | None = None,
     reserve_tokens: int = 50_000,
     *,
     include_line_numbers: bool = False,
@@ -684,7 +683,7 @@ def check_files_size_limit(files: list[str], max_tokens: int, threshold_percent:
     return within_limit, total_estimated_tokens, file_count
 
 
-def read_json_file(file_path: str) -> Optional[dict]:
+def read_json_file(file_path: str) -> dict | None:
     """
     Read and parse a JSON file with proper error handling.
 
@@ -778,7 +777,7 @@ def is_text_file(file_path: str) -> bool:
     return check_text_type(file_path)
 
 
-def read_file_safely(file_path: str, max_size: int = 10 * 1024 * 1024) -> Optional[str]:
+def read_file_safely(file_path: str, max_size: int = 10 * 1024 * 1024) -> str | None:
     """
     Read a file with size limits and encoding handling.
 
@@ -803,7 +802,7 @@ def read_file_safely(file_path: str, max_size: int = 10 * 1024 * 1024) -> Option
         return None
 
 
-def check_total_file_size(files: list[str], model_name: str) -> Optional[dict]:
+def check_total_file_size(files: list[str], model_name: str) -> dict | None:
     """
     Check if total file sizes would exceed token threshold before embedding.
 
diff --git a/utils/model_context.py b/utils/model_context.py
index c4015cc50..322c84cd9 100644
--- a/utils/model_context.py
+++ b/utils/model_context.py
@@ -28,7 +28,7 @@
 
 import logging
 from dataclasses import dataclass
-from typing import Any, Optional
+from typing import Any
 
 from config import DEFAULT_MODEL
 from providers import ModelCapabilities, ModelProviderRegistry
@@ -60,7 +60,7 @@ class ModelContext:
     token calculations, ensuring consistency across the system.
     """
 
-    def __init__(self, model_name: str, model_option: Optional[str] = None):
+    def __init__(self, model_name: str, model_option: str | None = None):
         self.model_name = model_name
         self.model_option = model_option  # Store optional model option (e.g., "for", "against", etc.)
         self._provider = None
@@ -93,7 +93,7 @@ def capabilities(self) -> ModelCapabilities:
             self._capabilities = self.provider.get_capabilities(self.model_name)
         return self._capabilities
 
-    def calculate_token_allocation(self, reserved_for_response: Optional[int] = None) -> TokenAllocation:
+    def calculate_token_allocation(self, reserved_for_response: int | None = None) -> TokenAllocation:
         """
         Calculate token allocation based on model capacity and conversation requirements.
 
diff --git a/utils/model_restrictions.py b/utils/model_restrictions.py
index c06839156..25bd0c3c7 100644
--- a/utils/model_restrictions.py
+++ b/utils/model_restrictions.py
@@ -22,7 +22,6 @@
 
 import logging
 from collections import defaultdict
-from typing import Optional
 
 from providers.shared import ProviderType
 from utils.env import get_env
@@ -125,7 +124,7 @@ def validate_against_known_models(self, provider_instances: dict[ProviderType, a
                         f"Please check for typos. Known models: {sorted(supported_models)}"
                     )
 
-    def is_allowed(self, provider_type: ProviderType, model_name: str, original_name: Optional[str] = None) -> bool:
+    def is_allowed(self, provider_type: ProviderType, model_name: str, original_name: str | None = None) -> bool:
         """
         Check if a model is allowed for a specific provider.
 
@@ -189,7 +188,7 @@ def is_allowed(self, provider_type: ProviderType, model_name: str, original_name
 
         return False
 
-    def get_allowed_models(self, provider_type: ProviderType) -> Optional[set[str]]:
+    def get_allowed_models(self, provider_type: ProviderType) -> set[str] | None:
         """
         Get the set of allowed models for a provider.
 
@@ -247,7 +246,7 @@ def get_restriction_summary(self) -> dict[str, any]:
 
 
 # Global instance (singleton pattern)
-_restriction_service: Optional[ModelRestrictionService] = None
+_restriction_service: ModelRestrictionService | None = None
 
 
 def get_restriction_service() -> ModelRestrictionService:
diff --git a/utils/storage_backend.py b/utils/storage_backend.py
index 1327a4776..ab8a63e21 100644
--- a/utils/storage_backend.py
+++ b/utils/storage_backend.py
@@ -21,7 +21,6 @@
 import logging
 import threading
 import time
-from typing import Optional
 
 from utils.env import get_env
 
@@ -56,7 +55,7 @@ def set_with_ttl(self, key: str, ttl_seconds: int, value: str) -> None:
             self._store[key] = (value, expires_at)
             logger.debug(f"Stored key {key} with TTL {ttl_seconds}s")
 
-    def get(self, key: str) -> Optional[str]:
+    def get(self, key: str) -> str | None:
         """Retrieve value if not expired"""
         with self._lock:
             if key in self._store:
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 000000000..987e19e36
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,1515 @@
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+revision = 3
+requires-python = ">=3.12"
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