research-driven-planninglisted

# Research-Driven Planning (Loop 1) ## Purpose Comprehensive planning with research-backed solutions and iterative risk mitigation that prevents 85-95% of problems before coding begins. ## Specialist Agent Coordination I coordinate multi-agent research and planning swarms using **explicit agent SOPs** from Claude-Flow's 86-agent ecosystem. **Methodology** (SOP: Specification → Research → Planning → Execution → Knowledge): 1. **Specification Phase**: Requirements capture with structured SPEC.md 2. **Research Phase**: 6-agent parallel research with self-consistency validation 3. **Planning Phase**: MECE task decomposition with research integration 4. **Execution Phase**: 8-agent Byzantine consensus pre-mortem (5 iterations) 5. **Knowledge Phase**: Planning package generation for Loop 2 integration **Integration**: Loop 1 of 3. Feeds → `parallel-swarm-implementation` (Loop 2), Receives ← `cicd-intelligent-recovery` (Loop 3) failure patterns. --- ## When to Use This Skill Activate this skill when: - Starting a new feature or project requiring comprehensive planning - Need to prevent problems before coding begins (85-95% failure prevention) - Want research-backed solutions instead of assumptions (30-60% time savings) - Require risk analysis with <3% failure confidence - Building something complex with multiple failure modes - Need evidence-based planning that feeds into implementation **DO NOT** use this skill for: - Quick fixes or trivial changes (use direct implementat