- Convert all markdown files from Chinese to English
- Remove all emoji/icon decorations (🔧📋⚙️✅🏁🔍📚⛔⭐)
- Update all section headers, descriptions, and documentation
- Keep all content logic, structure, code examples unchanged
- Maintain template variables and file paths as-is
Files converted (9 files total):
- SKILL.md: Output structure comments
- templates/skill-md.md: All Chinese descriptions and comments
- specs/reference-docs-spec.md: All section headers and explanations
- phases/01-requirements-discovery.md through 05-validation.md (5 files)
- specs/execution-modes.md, skill-requirements.md, cli-integration.md, scripting-integration.md (4 files)
- templates/sequential-phase.md, autonomous-orchestrator.md, autonomous-action.md, code-analysis-action.md, llm-action.md, script-template.md (6 files)
All 16 files in skill-generator are now fully in English.
- Updated orchestrator decision logic to improve state management and action selection.
- Introduced structured termination checks and action selection criteria.
- Enhanced state update mechanism with sliding window for action history and error tracking.
- Revised problem taxonomy for skill execution issues, consolidating categories and refining detection patterns.
- Improved severity calculation method for issue prioritization.
- Streamlined fix mapping strategies for better clarity and usability.
- Introduced Phase 2.5: Consolidation Agent to summarize analysis outputs and generate design overviews.
- Added Phase 4: Document Assembly to create index-style documents linking chapter files.
- Implemented Phase 5: Compliance Review & Iterative Refinement for CPCC compliance checks and updates.
- Established CPCC Compliance Requirements document outlining mandatory sections and validation functions.
- Created a base template for analysis agents to ensure consistency and efficiency in execution.
- Introduced a comprehensive code analysis action template for integrating code exploration and analysis capabilities.
- Added LLM action template for seamless integration of LLM calls with customizable prompts and tools.
- Implemented a benchmark search script to compare multiple search methods across various dimensions including speed, result quality, ranking stability, and coverage.
- Provided preset configurations for common analysis tasks and LLM actions, enhancing usability and flexibility.
- Introduced a comprehensive template for autonomous actions, detailing structure, execution, and error handling.
- Added an orchestrator template to manage state and decision logic for autonomous actions.
- Created a sequential phase template to outline execution steps and objectives for structured workflows.
- Developed a skill documentation template to standardize the generation of skill entry files.
- Implemented a Python script to compare search results between hybrid and cascade methods, analyzing ranking changes.
