v0.1.7 — Documentation Audit & Version Sync

What's Changed

Documentation Audit

• Version synchronized to 0.1.7 across all files: pyproject.toml, __init__.py, README.md, AGENTS.md, PAI.md, SPEC.md, CLAUDE.md, TO-DO.md, src/README.md, src/AGENTS.md, docs/modules/README.md
• Module count corrected from stale values (78, 80, 82+, 83) to verified 82 across 15+ documentation files
• 21 missing modules added to AGENTS.md Module Discovery section
• CHANGELOG.md updated with v0.1.7 entry

Script Refactoring

• Refactored audit/update scripts to thin orchestrator pattern delegating to maintenance library
• Deleted 62 dead documentation scripts from documentation/scripts/
• Added 4 new library modules: documentation/audit.py, documentation/maintenance.py, documentation/pai.py, static_analysis/__init__.py

Fixes

• SPEC.md version was stale at v0.1.1
• __init__.py version was stale at 0.1.6
• src/README.md version was stale at v0.1.6
• Removed accidentally duplicated Surface table from PAI.md

Full Changelog: v0.1.6...v0.1.7

v0.1.6: Agent Protocol, Memory Wiring, EventBus↔Orchestrator

v0.1.6 — Agent & Memory Foundations

Theme: "Solid Agent Bones"

Agent Protocol (agents/core/)

• AgentProtocol with plan()/act()/observe() lifecycle methods
• AgentMessage dataclass with typed roles, tool calls, and serialization
• ToolRegistry.from_mcp() bridge for MCP→agent tool integration
• ReActAgent.llm_client type-hinted as BaseLLMClient | Any

Memory Wiring (agentic_memory/)

• VectorStoreMemory auto-creates InMemoryVectorStore when none provided
• VectorStoreMemory.from_chromadb() optional factory
• AgentMemory.add() alias for MCP tool compatibility
• JSONFileStore.list_all() + thread-safe writes via threading.Lock
• UserProfile dataclass with ~/.codomyrmex/user_profile.json persistence

EventBus ↔ Orchestrator (events/, orchestrator/)

• EventBus.emit_typed() and subscribe_typed() convenience methods
• orchestrator_events.py with 7 typed event factory functions
• Workflow.run() emits lifecycle events via optional event_bus parameter

Visualization (data_visualization/)

• BasePlot enhanced with __str__/__repr__/save()/to_dict()
• BarChart/LinePlot upgraded to real matplotlib renderers
• RadarChart fixed to properly inherit from BasePlot
• All 19 plot subclasses call super().__init__()
• Full submodule exports: 19 plots, 14 components, 5 reports

Tests (49 new, zero mocks)

• test_agent_protocol.py (20 tests)
• test_memory_integration.py (12 tests)
• test_event_orchestrator.py (17 tests)
• test_enhanced_methods.py (22 visualization tests)

94 files changed, +2,846 / -1,006

v0.1.2: PAI Integration & Documentation Suite

What's New in v0.1.2

Added

• MCP HTTP transport with FastAPI server and 33 registered tools
• Web UI for interactive MCP tool testing
• PAI integration documentation suite (docs/pai/)
• Skills documentation suite (docs/skills/)
• UOR (Universal Object Reference) module with PrismEngine, EntityManager, UORGraph
• Model evaluation metrics module
• Data visualization modules: bar charts, line plots, components, reports
• Claude integration tests and UOR test suite
• Backward-compatibility shims for cerebrum visualization and agents education
• Comprehensive GitHub workflow suite for CI/CD
• RASP documentation pattern across all 78 modules

Changed

• Migrated dependency management to UV
• Standardized test paths to src/codomyrmex/tests/
• PAI.md files for all 78 modules updated with accurate exports
• Rate limiter enhanced with consume() method and initial_tokens parameter
• Skills, security governance, and telemetry module exports refined

Fixed

• All test failures resolved: documentation accuracy, security integration, curriculum, and git operations tests
• Version string consistency across all config files
• Module count inconsistencies resolved
• Stale files deep_audit.py and polish_exports.py removed

Full Changelog: v0.1.1...v0.1.2

v0.1.1: PAI Integration Documentation Suite

What's New in v0.1.1

This release honors the deep connection and integration between Codomyrmex and Daniel Miessler's Personal AI Infrastructure (PAI).

PAI Documentation Suite (11 files)

A comprehensive, modular documentation suite for the bidirectional PAI ↔ Codomyrmex integration:

Document	Content
README.md	Bidirectional architecture, 16-principle mapping, quick start
ARCHITECTURE.md	Three-layer deep dive (PAIBridge → MCPBridge → TrustGateway)
FLOWS.md	6 Mermaid diagrams for operational sequences
SIGNPOSTS.md	Line-level code pointers to 60+ symbols
AGENTS.md	Agent coordination guide
ALGORITHM.md	The Algorithm v0.2.25 (7 phases, ISC, depth levels)
SKILLS.md	Skill System architecture and priority hierarchy
TELOS.md	Deep Goal Understanding (10 identity files)
HOOKS.md	Hook System (8 event types, FormatReminder)
WORKFLOWS.md	Workflows and Dispatch v3.2.1
UPSTREAM_ISSUE.md	Community issue submission for PAI upstream

Version Bump

Core version bumped from 0.1.0 to 0.1.1:

• pyproject.toml
• src/codomyrmex/__init__.py
• src/codomyrmex/agents/pai/mcp_bridge.py
• SPEC.md

Links

• PAI Documentation
• PAI Upstream
• Full Diff

Codomyrmex v0.1.0 - Foundation & Expansion

Codomyrmex v0.1.0 - Foundation & Expansion

This is the first major release of Codomyrmex, standardizing the modular architecture and expanding IDE integration.

Major Accomplishments

Phase 1: Secure Cognitive Agent

• Established the core four-layer architecture.
• Implemented foundational logging, environment, and MCP protocols.
• Integrated the PAI (Personal AI Infrastructure) bridge for bidirectional agent interaction.

Phase 2: LLM Subsystem Strengthening

• Hardened LLM provider logic (OpenRouter, OpenAI, Anthropic, Gemini).
• Achieved 100% unit test pass rate with a "Zero-Mock" verification policy.
• Implemented robust performance monitoring and visualization suites.

Phase 3: Module Expansion

• Finalized 105+ specialized modules for coding, analysis, and automation.
• Introduced 5 new high-value IDE slash commands for deeper integration.
• Standardized all versioning to v0.1.0 across the ecosystem.

Key Features

• Zero-Mock Policy: Real functional verification across all modules.
• Deep PAI Integration: Seamless connection to Personal AI Infrastructure.
• Unified IDE Interface: Multi-workflow slash commands for project analysis and memory.