- Updated lifecycle requirements in issue creation to include new fields for testing, regression, acceptance, and commit strategies.
- Enhanced the planning command to generate structured output and handle multi-solution scenarios.
- Improved queue formation logic to ensure valid DAG and conflict resolution.
- Introduced a new interactive issue management skill for CRUD operations, allowing users to manage issues through a menu-driven interface.
- Updated documentation across commands to reflect changes in task structure and output requirements.
- Changed queue structure from 'queue' to 'tasks' in various files for clarity.
- Updated CLI commands to reflect new task ID usage instead of queue ID.
- Enhanced queue management with new delete functionality for historical queues.
- Improved metadata handling and task execution tracking.
- Updated dashboard and issue manager views to accommodate new task structure.
- Bumped version to 6.3.8 in package.json and package-lock.json.
- Added internationalization support for new issue and solution-related strings in i18n.js.
- Implemented a solution detail modal in issue-manager.js to display solution information and bind/unbind actions.
- Enhanced the skill loading function to combine project and user skills in hook-manager.js.
- Improved queue rendering logic to handle empty states and display queue statistics in issue-manager.js.
- Introduced command modals for queue operations, allowing users to generate execution queues via CLI commands.
- Added functionality to auto-generate issue IDs and regenerate them in the create issue modal.
- Implemented detailed rendering of solution tasks, including acceptance criteria and modification points.
- Added `/issue:manage` command for interactive issue management via CLI.
- Implemented features for listing, viewing, editing, deleting, and bulk operations on issues.
- Integrated GitHub issue fetching and text description parsing for issue creation.
- Enhanced user experience with menu-driven interface and structured output.
- Created helper functions for parsing user input and managing issue data.
- Added error handling and related command references for better usability.
feat(issue-creation): Introduce structured issue creation from GitHub URL or text description
- Added `/issue:new` command to create structured issues from GitHub issues or text descriptions.
- Implemented parsing logic for extracting key elements from issue descriptions.
- Integrated user confirmation for issue creation with options to edit title and priority.
- Ensured proper writing of issues to `.workflow/issues/issues.jsonl` with metadata.
- Included examples and error handling for various input scenarios.
- Implemented a new CLI Stream Viewer to display real-time output from CLI executions.
- Added state management for CLI executions, including handling of start, output, completion, and errors.
- Introduced UI rendering for stream tabs and content, with auto-scroll functionality.
- Integrated keyboard shortcuts for toggling the viewer and handling user interactions.
feat: create Issue Manager view for managing issues and execution queue
- Developed the Issue Manager view to manage issues, solutions, and execution queue.
- Implemented data loading functions for fetching issues and queue data from the API.
- Added filtering and rendering logic for issues and queue items, including drag-and-drop functionality.
- Created detail panel for viewing and editing issue details, including tasks and solutions.
- Added `/issue:plan` command to generate a structured task plan from GitHub issues or descriptions, including delivery and pause criteria, and a dependency graph.
- Introduced JSONL schema for task entries to enforce structure and validation.
- Developed comprehensive issue command with functionalities for initializing, listing, adding, updating, and exporting tasks.
- Implemented error handling and user feedback for various operations within the issue management workflow.
- Enhanced task management with priority levels, phase results, and executor preferences.
- Removed agent references in context-gather and test-context-gather commands for clarity.
- Updated test-task-generate to streamline agent configuration references.
- Enhanced action-planning-agent documentation by removing redundant examples.
- Adjusted execute command to eliminate direct agent path references.
- Improved context-gather documentation to clarify agent autonomy and project.json integration.
- Revised test-context-gather to focus on agent delegation and coverage analysis.
- Cleaned up test-task-generate to focus on task generation rules without direct agent references.
- Implemented automatic agent assignment based on exploration file names in deep analysis phase.
- Expanded project exploration phase to include intelligent angle selection based on software type.
- Enhanced output schemas and success criteria for exploration tasks to ensure clarity and completeness.
- Added integration tests for adaptive RRF weights in hybrid search.
- Enhanced query intent detection with new classifications: keyword, semantic, and mixed.
- Introduced symbol boosting in search results based on explicit symbol matches.
- Implemented embedding-based reranking with configurable options.
- Added global symbol index for efficient symbol lookups across projects.
- Improved file deletion handling on Windows to avoid permission errors.
- Updated chunk configuration to increase overlap for better context.
- Modified package.json test script to target specific test files.
- Created comprehensive writing style guidelines for documentation.
- Added TypeScript tests for query intent detection and adaptive weights.
- Established performance benchmarks for global symbol indexing.
- 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.
- Introduced a `stream` parameter to control output streaming vs. caching.
- Enhanced status determination logic to prioritize valid output over exit codes.
- Updated output structure to include full stdout and stderr when not streaming.
feat(cli-history-store): extend conversation turn schema and migration
- Added `cached`, `stdout_full`, and `stderr_full` fields to the conversation turn schema.
- Implemented database migration to add new columns if they do not exist.
- Updated upsert logic to handle new fields.
feat(codex-lens): implement global symbol index for fast lookups
- Created `GlobalSymbolIndex` class to manage project-wide symbol indexing.
- Added methods for adding, updating, and deleting symbols in the global index.
- Integrated global index updates into directory indexing processes.
feat(codex-lens): optimize search functionality with global index
- Enhanced `ChainSearchEngine` to utilize the global symbol index for faster searches.
- Added configuration option to enable/disable global symbol indexing.
- Updated tests to validate global index functionality and performance.
- Added search limit, content length, and extra files input fields in the CodexLens manager UI.
- Updated API request parameters to include new fields: max_content_length and extra_files_count.
- Refactored smart-search.ts to support new parameters with default values.
- Implemented result splitting logic to return both full content and additional file paths.
- Updated CLI commands to remove worker limits and allow dynamic scaling based on endpoint count.
- Introduced EmbeddingPoolConfig for improved embedding management and auto-discovery of providers.
- Enhanced search engines to utilize new parameters for fuzzy and exact searches.
- Added support for embedding single texts in the LiteLLM embedder.
- Added JSON-based settings management in Config class for embedding and LLM configurations.
- Introduced methods to save and load settings from a JSON file.
- Updated BaseEmbedder and its subclasses to include max_tokens property for better token management.
- Enhanced chunking strategy to support recursive splitting of large symbols with improved overlap handling.
- Implemented comprehensive tests for recursive splitting and chunking behavior.
- Added CLI tools configuration management for better integration with external tools.
- Introduced a new command for compacting session memory into structured text for recovery.
- Updated embedding_manager.py to include backend parameter in model configuration.
- Modified model_manager.py to utilize cache_name for ONNX models.
- Refactored hybrid_search.py to improve embedder initialization based on backend type.
- Added backend column to vector_store.py for better model configuration management.
- Implemented migration for existing database to include backend information.
- Enhanced API settings implementation with comprehensive provider and endpoint management.
- Introduced LiteLLM integration guide detailing configuration and usage.
- Added examples for LiteLLM usage in TypeScript.
- Introduced a new CodexLens Manager item in the dashboard for easier access.
- Implemented GPU management commands in the CLI, including listing available GPUs, selecting a specific GPU, and resetting to automatic detection.
- Enhanced the embedding generation process to utilize GPU resources more effectively, including batch size optimization for better performance.
- Updated the embedder to support device ID options for GPU selection, ensuring compatibility with DirectML and CUDA.
- Added detailed logging and error handling for GPU detection and selection processes.
- Updated package version to 6.2.9 and added comprehensive documentation for Codex Agent Execution Protocol.
- Introduced `execute.md` for sequential task execution from session folder with detailed execution rules, task tracking, and error handling.
- Added `lite-execute.md` for lightweight task execution from a JSON plan file, emphasizing serial execution and dependency management.
- Updated the dashboard template to hide the Code Graph Explorer feature.
- Enhanced the `executeCodexLens` function to use `exec` for better cross-platform compatibility and improved command execution.
- Changed the default `maxResults` and `limit` parameters in the smart search tool to 10 for better performance.
- Introduced a new `priority` search mode in the smart search tool, replacing the previous `parallel` mode, which now follows a fallback strategy: hybrid -> exact -> ripgrep.
- Optimized the embedding generation process in the embedding manager by batching operations and using a cached embedder instance to reduce model loading overhead.
- Implemented a thread-safe singleton pattern for the embedder to improve performance across multiple searches.
- Add Session ID and Project Root fields for workflow tracking
- Split Active Files into Working Files (modified) and Reference Files (read-only)
- Use absolute paths for all file references
- Support multiple plan sources: workflow/todo/user-stated/inferred
- Preserve complete execution plan verbatim without summarization
- Add path resolution rules and reference file categories
- Update quality checklist with new validation criteria
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added ANNIndex class for approximate nearest neighbor search using HNSW.
- Integrated ANN index with VectorStore for enhanced search capabilities.
- Updated test suite for ANN index, including tests for adding, searching, saving, and loading vectors.
- Modified existing tests to accommodate changes in search performance expectations.
- Improved error handling for file operations in tests to ensure compatibility with Windows file locks.
- Adjusted hybrid search performance assertions for increased stability in CI environments.
- Implemented core memory clustering visualization in core-memory-clusters.js
- Added functions for loading, rendering, and managing clusters and their members
- Created example hooks configuration in hooks-config-example.json for session management
- Developed test script for hooks integration in test-hooks.js
- Included error handling and notifications for user interactions
- Introduced styles for the help view including tab transitions, accordion animations, search highlighting, and responsive design.
- Implemented core memory styles with modal base styles, memory card designs, and knowledge graph visualization.
- Enhanced dark mode support across various components.
- Added loading states and empty state designs for better user experience.
- Updated command patterns across documentation and templates to reflect the new CLI syntax.
- Enhanced CLI tool implementation to support reading prompts from files and multi-line inputs.
- Modified core components and views to ensure compatibility with the new command structure.
- Adjusted help messages and internationalization strings to align with the updated command format.
- Improved error handling and user notifications in the CLI execution flow.
- Added core-memory.js and core-memory-graph.js for managing core memory views and visualizations.
- Introduced functions for viewing knowledge graphs and evolution history of memories.
- Implemented modal dialogs for creating, editing, and viewing memory details.
- Developed core-memory.ts for backend operations including list, import, export, and summary generation.
- Integrated Zod for parameter validation in core memory operations.
- Enhanced UI with dynamic rendering of memory cards and detailed views.
Ensure all agent executions wait for results before proceeding.
Modified 20 workflow command files with 32 Task call updates.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Simplify clarification question deduplication to use Claude's native intelligence
for identifying similar intents and merging questions across exploration angles.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
