- Create root-level directories: agents/, commands/, standards/, templates/ - Port 5 core standards from global Claude standards - Adapt standards for claude-skills context (cs-* prefix, Python tools, skills) - Create sprint planning documents (context.md, plan.md) - All directories tracked with .gitkeep files Standards created: - communication-standards.md (absolute honesty, zero fluff, pragmatic focus) - quality-standards.md (Python tool quality, agent workflows, testing) - git-workflow-standards.md (conventional commits, semantic versioning) - documentation-standards.md (Markdown standards, living docs, templates) - security-standards.md (secret detection, dependency security, input validation) Sprint plan ready for Days 1-6 implementation. Phase: 1 (Foundation) Issues: #8, #9
320 lines
9.2 KiB
Markdown
320 lines
9.2 KiB
Markdown
# Quality Standards
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## Core Quality Principles
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### **1. Quality-First Completion**
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- **Zero Defect Handoff:** No work considered complete with known quality issues
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- **Comprehensive Validation:** All acceptance criteria verified through testing
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- **Path Resolution:** All relative paths validated and working
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- **Tool Execution:** All Python tools tested and executing correctly
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### **2. Testing Standards**
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- **Python Tools:** All automation tools must execute without errors
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- **Agent Workflows:** Agent markdown files validated for completeness
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- **Integration Testing:** Agent-to-skill integration verified
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- **Documentation Quality:** All documentation clear, accurate, and actionable
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### **3. Code Quality**
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- **Python Standards:** PEP 8 compliance for all Python scripts
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- **No Hardcoded Secrets:** Use environment variables or configuration files
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- **Error Handling:** Proper exception handling in all tools
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- **Type Hints:** Use type annotations for Python functions
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## Universal Completion Criteria (ALL TASKS)
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```yaml
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functional_requirements:
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- [ ] All acceptance criteria satisfied with documented verification
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- [ ] Feature functionality validated in target environments
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- [ ] Edge cases identified and handled appropriately
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- [ ] Error scenarios tested with proper error handling
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- [ ] Integration points tested and validated
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quality_standards:
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- [ ] Code review completed with documented feedback
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- [ ] Automated tests passing where applicable
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- [ ] Manual testing completed for user-facing functionality
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- [ ] Documentation updated with changes
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- [ ] No broken links or missing references
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documentation_requirements:
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- [ ] Technical documentation updated with implementation details
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- [ ] User documentation updated with new functionality guidance
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- [ ] Change documentation prepared with impact analysis
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- [ ] Handoff documentation prepared with clear next steps
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```
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## Agent-Specific Quality Gates
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### **Agent Implementation Standards**
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```yaml
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agent_quality_validation:
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yaml_frontmatter:
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- [ ] Valid YAML syntax (no parsing errors)
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- [ ] All required fields present (name, description, skills, domain, model, tools)
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- [ ] cs-* prefix used for agent naming
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- [ ] Domain correctly categorized
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skill_integration:
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- [ ] Relative paths resolve correctly (../../ pattern)
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- [ ] Skill location documented and accessible
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- [ ] Python tools referenced with correct paths
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- [ ] Knowledge bases referenced with correct paths
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- [ ] Templates referenced with correct paths
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workflow_documentation:
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- [ ] Minimum 3 workflows documented
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- [ ] Each workflow has clear step-by-step instructions
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- [ ] Integration examples provided
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- [ ] Success metrics defined
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- [ ] Related agents cross-referenced
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testing_requirements:
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- [ ] Python tool execution tested from agent context
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- [ ] Relative path resolution verified
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- [ ] Knowledge base files accessible
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- [ ] All examples in documentation work
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- [ ] No broken markdown links
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```
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## Python Tool Quality Standards
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### **Python Script Requirements**
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```python
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# All Python tools must follow these standards
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"""
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Module: tool_name.py
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Description: [Clear description of what this tool does]
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Usage: python tool_name.py [arguments]
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"""
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from typing import Optional, List, Dict
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import sys
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import json
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def main(arg1: str, arg2: Optional[str] = None) -> int:
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"""
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Main function description.
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Args:
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arg1: Description of argument 1
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arg2: Description of optional argument 2
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Returns:
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Exit code (0 for success, 1 for error)
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"""
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try:
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# Tool implementation
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result = process_data(arg1, arg2)
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# Output results
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if json_output:
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print(json.dumps(result, indent=2))
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else:
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print(format_human_readable(result))
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return 0
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except Exception as e:
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print(f"Error: {e}", file=sys.stderr)
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return 1
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if __name__ == "__main__":
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sys.exit(main())
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```
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### **Python Quality Checklist**
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```yaml
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python_tool_quality:
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code_standards:
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- [ ] PEP 8 compliant (use pylint or flake8)
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- [ ] Type hints for all functions
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- [ ] Docstrings for all public functions
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- [ ] Clear error messages
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- [ ] Proper exception handling
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functionality:
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- [ ] Handles missing arguments gracefully
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- [ ] Provides helpful usage information (--help)
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- [ ] Supports both JSON and human-readable output
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- [ ] Returns appropriate exit codes
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- [ ] No hardcoded file paths (use relative or arguments)
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dependencies:
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- [ ] Uses standard library when possible
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- [ ] External dependencies documented in skill README
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- [ ] Requirements.txt provided if external packages needed
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- [ ] Version constraints specified for dependencies
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```
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## Documentation Quality Standards
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### **Markdown Documentation Requirements**
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```yaml
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documentation_quality:
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structure:
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- [ ] Clear hierarchy with proper headings
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- [ ] Table of contents for long documents
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- [ ] Consistent formatting throughout
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- [ ] Code blocks use appropriate syntax highlighting
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- [ ] Lists properly formatted
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content:
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- [ ] All links work (no 404s)
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- [ ] All code examples tested and working
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- [ ] All file paths are correct
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- [ ] Screenshots/diagrams up to date
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- [ ] No outdated information
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accessibility:
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- [ ] Alt text for images
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- [ ] Descriptive link text (not "click here")
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- [ ] Proper heading hierarchy (no skipping levels)
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- [ ] Code examples include explanatory text
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maintenance:
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- [ ] Date updated timestamp
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- [ ] Version information if applicable
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- [ ] Changelog for significant updates
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```
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## Quality Validation Commands
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### **Automated Quality Checks**
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```bash
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# Markdown linting
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yamllint agents/**/*.md standards/**/*.md documentation/**/*.md
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# Python syntax validation
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python -m compileall marketing-skill product-team c-level-advisor engineering-team ra-qm-team
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# Check for broken links (manual check required)
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# Verify all ../../ relative paths resolve
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# Test Python tools
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for script in $(find . -name "*.py" -path "*/scripts/*"); do
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echo "Testing: $script"
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python "$script" --help || echo "❌ Failed: $script"
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done
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```
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### **Manual Validation Checklist**
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```yaml
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pre_commit_validation:
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agent_files:
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- [ ] YAML frontmatter valid
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- [ ] All workflows documented
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- [ ] Integration examples present
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- [ ] No broken links
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- [ ] Relative paths verified
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python_tools:
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- [ ] Scripts execute without errors
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- [ ] --help flag works
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- [ ] Error handling tested
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- [ ] Output formats correct
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documentation:
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- [ ] README updated if needed
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- [ ] CLAUDE.md reflects changes
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- [ ] All examples tested
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- [ ] Changelog updated
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pre_push_validation:
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- [ ] All quality checks pass
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- [ ] No secrets in code
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- [ ] Commit messages follow convention
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- [ ] Branch protection requirements met
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```
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## Quality Metrics for Agents & Skills
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### **Success Criteria**
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```yaml
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agent_effectiveness:
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workflow_clarity:
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target: "Users can follow workflows without assistance"
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measurement: "Documentation completeness and clarity"
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tool_reliability:
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target: "100% of Python tools execute successfully"
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measurement: "Script execution success rate"
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path_resolution:
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target: "100% of relative paths resolve correctly"
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measurement: "Path validation tests passing"
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integration_quality:
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target: "Agents seamlessly invoke skills"
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measurement: "Agent-skill integration tests passing"
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documentation_quality:
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completeness:
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target: "All required sections present"
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measurement: "Documentation structure checklist"
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accuracy:
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target: "Zero broken links or outdated information"
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measurement: "Link validation and content review"
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usability:
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target: "Users can implement workflows in <30 minutes"
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measurement: "Time-to-implementation tracking"
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```
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## Quality Improvement Process
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### **Continuous Quality Enhancement**
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- **Pre-commit:** Validate syntax, check paths, test tools locally
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- **Pull Request:** Peer review, automated testing, quality gate checks
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- **Post-merge:** Monitor for issues, collect user feedback
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- **Monthly:** Review quality metrics, update standards as needed
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- **Quarterly:** Assess skill/agent effectiveness, plan improvements
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### **Quality Issue Resolution**
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```yaml
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issue_priority:
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P0_critical:
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- Broken Python tools (execution failures)
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- Invalid relative paths (404 errors)
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- Security vulnerabilities
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- Data loss or corruption
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response_time: "<1 hour"
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P1_high:
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- Broken workflows in agents
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- Documentation inaccuracies
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- Missing required sections
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- Performance issues
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response_time: "<24 hours"
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P2_medium:
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- Enhancement requests
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- Documentation improvements
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- Code refactoring
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- Optimization opportunities
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response_time: "<1 week"
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P3_low:
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- Nice-to-have features
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- Minor documentation updates
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- Style improvements
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response_time: "<1 month"
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```
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---
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**Focus**: Python tool quality, agent workflow clarity, skill integration testing
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**Updated**: November 2025
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**Review**: Monthly quality assessment
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**Compliance**: PEP 8, Markdown standards, relative path conventions
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