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Zhongwei Li
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commands/analyze/project.md
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145
commands/analyze/project.md
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name: analyze:project
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description: Autonomously analyze the project with automatic skill selection and pattern learning
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delegates-to: autonomous-agent:orchestrator
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# Auto-Analyze Command
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Analyze the current project autonomously using the orchestrator agent. This will:
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- Auto-detect project type and technologies
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- Load relevant skills based on project context
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- Run code analysis in background
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- Generate comprehensive quality report
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- Store learned patterns for future use
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The orchestrator will make all decisions autonomously without requiring confirmation at each step.
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## How It Works
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1. **Project Detection**: Analyzes project structure, files, and configuration
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2. **Context Analysis**: Determines project type, languages, and frameworks
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3. **Skill Loading**: Auto-selects relevant skills based on context
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4. **Analysis Execution**: Runs comprehensive code analysis
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5. **Pattern Learning**: Stores successful approaches for future similar projects
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6. **Report Generation**: Creates detailed analysis report
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**IMPORTANT**: When delegating this command to the orchestrator agent, the agent MUST:
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1. Show concise terminal output (15-20 lines max) with top 3 findings and recommendations
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2. Save detailed report to `.claude/data/reports/auto-analyze-YYYY-MM-DD.md` with ALL findings
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3. Include file path in terminal output
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4. Never complete silently, never show 50+ lines in terminal
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## Usage
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```bash
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/analyze:project
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```
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## Example Output
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The orchestrator MUST use two-tier presentation:
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### Terminal Output (Concise)
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```
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[PASS] Auto-Analyze Complete - Quality: 88/100
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Key Findings:
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* Python/FastAPI project, 127 files analyzed
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* 4 failing tests in auth module
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* 12 functions missing docstrings
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Top Recommendations:
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1. [HIGH] Fix failing auth tests -> +4 quality points
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2. [MED] Add docstrings to public APIs
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3. [MED] Refactor high-complexity functions
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📄 Full report: .claude/data/reports/analyze-project-2025-10-21.md
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⏱ Completed in 2.3 minutes
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```
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### File Report (Detailed)
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Saved to `.claude/data/reports/analyze-project-2025-10-21.md`:
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```
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=======================================================
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AUTO-ANALYZE DETAILED REPORT
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=======================================================
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Generated: 2025-10-21 14:30:00
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+- Project Context ------------------------------------+
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| Type: Python project with FastAPI framework |
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| Languages: Python 3.9+ |
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| Frameworks: FastAPI, SQLAlchemy, Pydantic |
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| Total Files: 127 |
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| Lines of Code: 12,450 |
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+-------------------------------------------------------+
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+- Quality Assessment ---------------------------------+
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| Overall Score: 88/100 [PASS] |
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| Tests: 45 tests, 92% passing (41/45) |
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| Coverage: 82% |
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| Standards: 89% compliant |
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| Documentation: 85% complete |
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| Pattern Adherence: 95% |
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+-------------------------------------------------------+
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+- Strengths ------------------------------------------+
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| * Well-structured API endpoints |
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| * Good test coverage on core modules |
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| * Consistent coding style |
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| * Clear separation of concerns |
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| * Effective use of Pydantic for validation |
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+-------------------------------------------------------+
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+- Issues Found ---------------------------------------+
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| Tests: |
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| * test_user_login() - AssertionError (auth.py:45) |
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| * test_token_refresh() - Timeout (auth.py:89) |
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| * test_logout() - Connection error (auth.py:112) |
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| * test_password_reset() - Invalid state (auth.py:145)|
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| |
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| Documentation: |
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| * 12 functions missing docstrings |
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| * API endpoint documentation incomplete |
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| |
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| Complexity: |
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| * get_user_permissions() - Cyclomatic: 18 (auth.py) |
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| * validate_token() - Cyclomatic: 16 (auth.py) |
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| * process_payment() - Cyclomatic: 15 (payment.py) |
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+-------------------------------------------------------+
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+- All Recommendations --------------------------------+
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| 1. [HIGH] Fix 4 failing tests in auth module |
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| -> Expected quality impact: +4 points |
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| -> Run /quality-check for auto-fix |
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| |
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| 2. [MED] Add docstrings to 12 public functions |
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| -> Improves maintainability and API documentation |
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| -> Expected quality impact: +2 points |
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| |
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| 3. [MED] Refactor 3 high-complexity functions |
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| -> Target: get_user_permissions(), validate_token()|
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| -> Expected quality impact: +2 points |
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| |
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| 4. [LOW] Complete API endpoint documentation |
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| -> Add OpenAPI descriptions |
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| -> Expected quality impact: +1 point |
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+-------------------------------------------------------+
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Skills Loaded: code-analysis, quality-standards, pattern-learning
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Agents Used: autonomous-agent:code-analyzer, autonomous-agent:background-task-manager
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Patterns Stored: 1 new pattern in .claude-patterns/
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Analysis Time: 2.3 minutes
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=======================================================
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```
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## See Also
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- `/analyze:quality` - Comprehensive quality control with auto-fix
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- `/learn:init` - Initialize pattern learning database
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---
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