* Migration from docker to standalone server
Migration handling
Fixed tests
Use simpler in-memory storage
Support for concurrent logging to disk
Simplified direct connections to localhost
* Migration from docker / redis to standalone script
Updated tests
Updated run script
Fixed requirements
Use dotenv
Ask if user would like to install MCP in Claude Desktop once
Updated docs
* More cleanup and references to docker removed
* Cleanup
* Comments
* Fixed tests
* Fix GitHub Actions workflow for standalone Python architecture
- Install requirements-dev.txt for pytest and testing dependencies
- Remove Docker setup from simulation tests (now standalone)
- Simplify linting job to use requirements-dev.txt
- Update simulation tests to run directly without Docker
Fixes unit test failures in CI due to missing pytest dependency.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Remove simulation tests from GitHub Actions
- Removed simulation-tests job that makes real API calls
- Keep only unit tests (mocked, no API costs) and linting
- Simulation tests should be run manually with real API keys
- Reduces CI costs and complexity
GitHub Actions now only runs:
- Unit tests (569 tests, all mocked)
- Code quality checks (ruff, black)
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Fixed tests
* Fixed tests
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Co-authored-by: Claude <noreply@anthropic.com>
* WIP
Refactor resolving mode_names, should be done once at MCP call boundary
Pass around model context instead
Consensus tool allows one to get a consensus from multiple models, optionally assigning one a 'for' or 'against' stance to find nuanced responses.
* Deduplication of model resolution, model_context should be available before reaching deeper parts of the code
Improved abstraction when building conversations
Throw programmer errors early
* Guardrails
Support for `model:option` format at MCP boundary so future tools can use additional options if needed instead of handling this only for consensus
Model name now supports an optional ":option" for future use
* Simplified async flow
* Improved model for request to support natural language
Simplified async flow
* Improved model for request to support natural language
Simplified async flow
* Fix consensus tool async/sync patterns to match codebase standards
CRITICAL FIXES:
- Converted _get_consensus_responses from async to sync (matches other tools)
- Converted store_conversation_turn from async to sync (add_turn is synchronous)
- Removed unnecessary asyncio imports and sleep calls
- Fixed ClosedResourceError in MCP protocol during long consensus operations
PATTERN ALIGNMENT:
- Consensus tool now follows same sync patterns as all other tools
- Only execute() and prepare_prompt() are async (base class requirement)
- All internal operations are synchronous like analyze, chat, debug, etc.
TESTING:
- MCP simulation test now passes: consensus_stance ✅
- Two-model consensus works correctly in ~35 seconds
- Unknown stance handling defaults to neutral with warnings
- All 9 unit tests pass (100% success rate)
The consensus tool async patterns were anomalous in the codebase.
This fix aligns it with the established synchronous patterns used
by all other tools while maintaining full functionality.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Fixed call order and added new test
* Cleanup dead comments
Docs for the new tool
Improved tests
---------
Co-authored-by: Claude <noreply@anthropic.com>
Docs added to show how a new tool is created
All tools should add numbers to code for models to be able to reference if needed
Enabled line numbering for code for all tools to use
Additional tests to validate line numbering is not added to git diffs
Supports decomposing large components and files, finding codesmells, finding modernizing opportunities as well as code organization opportunities. Fix this mega-classes today!
Line numbers added to embedded code for better references from model -> claude
- Added o3-pro codereview tests for both direct OpenAI and OpenRouter paths
- Updated validation criteria to account for additional test cases (5 total calls)
- Addresses Gemini Code Assist feedback about incomplete test coverage
- Ensures o3-pro functionality is thoroughly validated across all tools
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Added o3-pro model configuration to custom_models.json with 200K context
- Updated OpenAI provider to support o3-pro with fixed temperature constraint
- Extended simulator tests to include o3-pro validation scenarios
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Further fixes to tests
Pass O3 simulation test when keys are not set, along with a notice
Updated docs on testing, simulation tests / contributing
Support for OpenAI o4-mini and o4-mini-high
* Support for Custom URLs and custom models, including locally hosted models such as ollama
* Support for native + openrouter + local models (i.e. dozens of models) means you can start delegating sub-tasks to particular models or work to local models such as localizations or other boring work etc.
* Several tests added
* precommit to also include untracked (new) files
* Logfile auto rollover
* Improved logging
Simulation tests to confirm threading and history traversal
Chain of communication and branching validation tests from live simulation
Temperature enforcement per model
## Major Features Added
### 🎯 Dynamic Configuration System
- **Environment-aware model selection**: DEFAULT_MODEL with 'pro'/'flash' shortcuts
- **Configurable thinking modes**: DEFAULT_THINKING_MODE_THINKDEEP for extended reasoning
- **All tool schemas now dynamic**: Show actual current defaults instead of hardcoded values
- **Enhanced setup workflow**: Copy from .env.example with smart customization
### 🔧 Model & Thinking Configuration
- **Smart model resolution**: Support both shortcuts ('pro', 'flash') and full model names
- **Thinking mode optimization**: Only apply thinking budget to models that support it
- **Flash model compatibility**: Works without thinking config, still beneficial via system prompts
- **Dynamic schema descriptions**: Tool parameters show current environment values
### 🚀 Enhanced Developer Experience
- **Fail-fast Docker setup**: GEMINI_API_KEY required upfront in docker-compose
- **Comprehensive startup logging**: Shows current model and thinking mode defaults
- **Enhanced get_version tool**: Reports all dynamic configuration values
- **Better .env documentation**: Clear token consumption details and model options
### 🧪 Comprehensive Testing
- **Live model validation**: New simulator test validates Pro vs Flash thinking behavior
- **Dynamic configuration tests**: Verify environment variable overrides work correctly
- **Complete test coverage**: All 139 unit tests pass, including new model config tests
### 📋 Configuration Files Updated
- **docker-compose.yml**: Fail-fast API key validation, thinking mode support
- **setup-docker.sh**: Copy from .env.example instead of manual creation
- **.env.example**: Detailed documentation with token consumption per thinking mode
- **.gitignore**: Added test-setup/ for cleanup
### 🛠 Technical Improvements
- **Removed setup.py**: Fully Docker-based deployment (no longer needed)
- **REDIS_URL smart defaults**: Auto-configured for Docker, still configurable for dev
- **All tools updated**: Consistent dynamic model parameter descriptions
- **Enhanced error handling**: Better model resolution and validation
## Breaking Changes
- Removed setup.py (Docker-only deployment)
- Model parameter descriptions now show actual defaults (dynamic)
## Migration Guide
- Update .env files using new .env.example format
- Use 'pro'/'flash' shortcuts or full model names
- Set DEFAULT_THINKING_MODE_THINKDEEP for custom thinking depth
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
