feat: add minimal feedback collection tool

- Add feedback tool that sends data to API endpoint
- No LangSmith integration - just API calls
- Simple validation with Pydantic
- Auto-included in StackOneToolSet
- 6 focused tests covering validation, execution, and integration

Author: NicolasBelissent

stackone_ai/feedback/__init__.py

@@ -0,0 +1,5 @@
+"""Feedback collection tools for StackOne."""
+
+from .tool import create_feedback_tool
+
+__all__ = ["create_feedback_tool"]

stackone_ai/feedback/tool.py

@@ -0,0 +1,160 @@
+"""Feedback collection tool for StackOne."""
+
+# TODO: Remove when Python 3.9 support is dropped
+from __future__ import annotations
+
+import json
+
+from pydantic import BaseModel, Field, field_validator
+
+from ..models import (
+    ExecuteConfig,
+    JsonDict,
+    ParameterLocation,
+    StackOneError,
+    StackOneTool,
+    ToolParameters,
+)
+
+
+class FeedbackInput(BaseModel):
+    """Input schema for feedback tool."""
+
+    feedback: str = Field(..., min_length=1, description="User feedback text")
+    account_id: str = Field(..., min_length=1, description="Account identifier")
+    tool_names: list[str] = Field(..., min_length=1, description="List of tool names")
+
+    @field_validator("feedback", "account_id")
+    @classmethod
+    def validate_non_empty_trimmed(cls, v: str) -> str:
+        """Validate that string is non-empty after trimming."""
+        trimmed = v.strip()
+        if not trimmed:
+            raise ValueError("Field must be a non-empty string")
+        return trimmed
+
+    @field_validator("tool_names")
+    @classmethod
+    def validate_tool_names(cls, v: list[str]) -> list[str]:
+        """Validate and clean tool names."""
+        cleaned = [name.strip() for name in v if name.strip()]
+        if not cleaned:
+            raise ValueError("At least one tool name is required")
+        return cleaned
+
+
+class FeedbackTool(StackOneTool):
+    """Extended tool for collecting feedback with enhanced validation."""
+
+    def execute(self, arguments: str | JsonDict | None = None) -> JsonDict:
+        """
+        Execute the feedback tool with enhanced validation.
+
+        Args:
+            arguments: Tool arguments as string or dict
+
+        Returns:
+            Response from the API
+
+        Raises:
+            StackOneError: If validation or API call fails
+        """
+        try:
+            # Parse input
+            if isinstance(arguments, str):
+                raw_params = json.loads(arguments)
+            else:
+                raw_params = arguments or {}
+
+            # Validate with Pydantic
+            parsed_params = FeedbackInput(**raw_params)
+
+            # Build validated request body
+            validated_arguments = {
+                "feedback": parsed_params.feedback,
+                "account_id": parsed_params.account_id,
+                "tool_names": parsed_params.tool_names,
+            }
+
+            # Use the parent execute method with validated arguments
+            return super().execute(validated_arguments)
+
+        except json.JSONDecodeError as exc:
+            raise StackOneError(f"Invalid JSON in arguments: {exc}") from exc
+        except ValueError as exc:
+            raise StackOneError(f"Validation error: {exc}") from exc
+        except Exception as error:
+            if isinstance(error, StackOneError):
+                raise
+            raise StackOneError(f"Error executing feedback tool: {error}") from error
+
+
+def create_feedback_tool(
+    api_key: str,
+    account_id: str | None = None,
+    base_url: str = "https://api.stackone.com",
+) -> FeedbackTool:
+    """
+    Create a feedback collection tool.
+
+    Args:
+        api_key: API key for authentication
+        account_id: Optional account ID
+        base_url: Base URL for the API
+
+    Returns:
+        FeedbackTool configured for feedback collection
+    """
+    name = "meta_collect_tool_feedback"
+    description = (
+        "Collects user feedback on StackOne tool performance. "
+        "First ask the user, \"Are you ok with sending feedback to StackOne?\" "
+        "and mention that the LLM will take care of sending it. "
+        "Call this tool only when the user explicitly answers yes."
+    )
+
+    parameters = ToolParameters(
+        type="object",
+        properties={
+            "account_id": {
+                "type": "string",
+                "description": 'Account identifier (e.g., "acc_123456")',
+            },
+            "feedback": {
+                "type": "string",
+                "description": "Verbatim feedback from the user about their experience with StackOne tools.",
+            },
+            "tool_names": {
+                "type": "array",
+                "items": {
+                    "type": "string",
+                },
+                "description": "Array of tool names being reviewed",
+            },
+        },
+    )
+
+    execute_config = ExecuteConfig(
+        name=name,
+        method="POST",
+        url=f"{base_url}/ai/tool-feedback",
+        body_type="json",
+        parameter_locations={
+            "feedback": ParameterLocation.BODY,
+            "account_id": ParameterLocation.BODY,
+            "tool_names": ParameterLocation.BODY,
+        },
+    )
+
+    # Create instance by calling parent class __init__ directly since FeedbackTool is a subclass
+    tool = FeedbackTool.__new__(FeedbackTool)
+    StackOneTool.__init__(
+        tool,
+        description=description,
+        parameters=parameters,
+        _execute_config=execute_config,
+        _api_key=api_key,
+        _account_id=account_id,
+    )
+
+    return tool

stackone_ai/toolset.py

@@ -170,6 +170,17 @@ def get_tools(
                         )
                         all_tools.append(tool)
 
+            # Add feedback collection meta tool
+            from .feedback import create_feedback_tool
+            feedback_tool_name = "meta_collect_tool_feedback"
+            if filter_pattern is None or self._matches_filter(feedback_tool_name, filter_pattern):
+                feedback_tool = create_feedback_tool(
+                    api_key=self.api_key,
+                    account_id=effective_account_id,
+                    base_url=self.base_url or "https://api.stackone.com",
+                )
+                all_tools.append(feedback_tool)
+
             return Tools(all_tools)
 
         except Exception as e: