Create implementation plan by synthesizing context, analysis, and template into a complete plan.json file.
Ask the user for the feature name (alphanumeric, hyphens, underscores only), then call the `mcp__docs-mcp__create_plan` tool with:
- project_path: current working directory
- feature_name: the user-provided feature name
This is a **meta-tool** that guides AI through plan generation by:
1. Loading context.json from user's project (from prior `/gather-context` if available)
2. Loading project analysis (from prior `/analyze-for-planning` if available)
3. Loading AI-optimized template from **MCP server's directory** (not user's project)
4. Returning all inputs to AI with synthesis instructions
5. AI generates complete 10-section plan
6. AI saves to coderef/working/{feature_name}/plan.json
Generation process:
- **AI synthesizes**: Tool provides inputs, AI creates the actual plan content
- **Context-aware**: Uses user's requirements and project analysis
- **Template-guided**: Follows planning-template-for-ai.json structure
- **Complete plans**: No placeholder TODOs, real implementation details
Returns:
- Plan file path
- Feature name
- Sections completed (0-10)
- Status: 'complete' | 'partial'
- Has context/analysis indicators
- Next steps recommendations
**Workflow integration**:
1. `/gather-context` - Gather feature requirements (optional but recommended)
2. `/analyze-for-planning` - Analyze project context (optional but recommended)
3. `/create-plan` - **Generate plan** ← You are here
4. `/validate-plan` - Validate plan quality (score 0-100)
5. `/generate-plan-review` - Generate markdown review report
**Important**: Best results require both context.json and project analysis. Tool will warn if either is missing.
