- Introduced comprehensive guidelines for generating implementation plan documents (IMPL_PLAN.md, task JSONs, TODO_LIST.md) using the action-planning-agent.
- Defined auto mode for user configuration with default settings.
- Outlined core philosophy emphasizing planning only, agent-driven document generation, and memory-first context loading.
- Detailed execution process divided into phases: User Configuration, Context Preparation, Single Agent Planning, N Parallel Planning, and Integration.
- Included lifecycle management for user configuration and agent interactions.
- Specified document generation lifecycle with clear expectations for outputs and quality standards.
- 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.
- Phase 3: Added Mermaid diagram generation for system architecture, function modules, algorithms, class diagrams, sequence diagrams, and error flows.
- Phase 4: Assembled analysis and diagrams into a structured CPCC-compliant document with section templates and figure numbering.
- Phase 5: Developed compliance review process with iterative refinement based on analysis findings and user feedback.
- Added CPCC compliance requirements and quality standards for project analysis reports.
- Established a comprehensive project analysis skill with detailed execution flow and report types.
- Enhanced error handling and recovery mechanisms throughout the analysis phases.
