checklist-generator

name	checklist-generator
description	Generate context-aware quality checklists for code review and QA using IEEE 1028 base standards plus LLM contextual additions
version	1
model	sonnet
invoked_by	both
user_invocable	true
tools	["Read","Write","Edit","Glob","Grep"]
best_practices	["Start with IEEE 1028 base checklist (80-90% coverage)","Add contextual items based on project type (10-20%)","Mark AI-generated items with [AI-GENERATED] prefix","Tailor checklist to current file types and frameworks","Return markdown checklist with checkboxes"]
error_handling	strict
streaming	supported

Quality Checklist Generator

Overview

Generate comprehensive, context-aware quality checklists combining IEEE 1028 standards (80-90%) with LLM-generated contextual items (10-20%). Ensures systematic quality validation before completion.

Core principle: Universal quality standards enhanced with project-specific context.

When to Use

Always:

• Before completing implementation tasks
• During code review
• QA validation phase
• Pre-commit verification
• Before marking tasks complete

Exceptions:

• Throwaway prototypes
• Configuration-only changes

Purpose

1. IEEE 1028 Base: Proven quality review standards (universal)
2. Contextual Enhancement: LLM adds project-specific items
3. Systematic Validation: Ensures comprehensive quality coverage

IEEE 1028 Base Categories

The following categories are included in every checklist (80-90% of items):

Code Quality

• Code follows project style guide
• No code duplication (DRY principle)
• Cyclomatic complexity < 10 per function
• Functions have single responsibility
• Variable names are clear and descriptive
• Magic numbers replaced with named constants
• Dead code removed

Testing

• Tests written first (TDD followed)
• All new code has corresponding tests
• Tests cover edge cases and error conditions
• Test coverage ≥ 80% for new code
• Integration tests for multi-component interactions
• Tests are isolated and don't depend on order

Security

• Input validation on all user inputs
• No SQL injection vulnerabilities
• No XSS vulnerabilities
• Sensitive data encrypted at rest and in transit
• Authentication and authorization checks present
• No hardcoded secrets or credentials
• OWASP Top 10 considered

Performance

• No obvious performance bottlenecks
• Database queries optimized (no N+1 queries)
• Appropriate caching used
• Resource cleanup (close connections, release memory)
• No infinite loops or recursion risks
• Large data operations paginated

Documentation