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https://github.com/catlog22/Claude-Code-Workflow.git
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99ee4e7d36
- Create task-schema.json (JSON Schema draft-07) with 10 field blocks fusing Unified JSONL, 6-field Task JSON, and Solution Schema advantages - Migrate unified-execute-with-file from JSONL to .task/*.json directory scanning - Migrate 3 producers (lite-plan, plan-converter, collaborative-plan) to .task/*.json multi-file output - Add review-cycle Phase 7.5 export-to-tasks (FIX-*.json) and issue-resolve --export-tasks option - Add schema compatibility annotations to action-planning-agent, workflow-plan, and tdd-plan - Add spec-generator skill phases and templates - Add memory v2 pipeline (consolidation, extraction, job scheduler, embedder) - Add secret-redactor utility and core-memory enhancements - Add codex-lens accuracy benchmarks and staged env config overrides
CodexLens
CodexLens is a multi-modal code analysis platform designed to provide comprehensive code understanding and analysis capabilities.
Features
- Multi-language Support: Analyze code in Python, JavaScript, TypeScript and more using Tree-sitter parsers
- Semantic Search: Find relevant code snippets using semantic understanding with fastembed and HNSWLIB
- Code Parsing: Advanced code structure parsing with tree-sitter
- Flexible Architecture: Modular design for easy extension and customization
Installation
Basic Installation
pip install codex-lens
With Semantic Search
pip install codex-lens[semantic]
With GPU Acceleration (NVIDIA CUDA)
pip install codex-lens[semantic-gpu]
With DirectML (Windows - NVIDIA/AMD/Intel)
pip install codex-lens[semantic-directml]
With All Optional Features
pip install codex-lens[full]
Requirements
- Python >= 3.10
- See
pyproject.tomlfor detailed dependency list
Development
This project uses setuptools for building and packaging.
License
MIT License
Authors
CodexLens Contributors