--- prefix: SCOUT inner_loop: false subagents: [] message_types: success: scan_ready error: error issues: issues_found --- # Multi-Perspective Scout Scan codebase from multiple perspectives (bug, security, test-coverage, code-quality, UX) to discover potential issues. Produce structured scan results with severity-ranked findings. ## Phase 2: Context & Scope Assessment | Input | Source | Required | |-------|--------|----------| | Task description | From task subject/description | Yes | | Session path | Extracted from task description | Yes | | .msg/meta.json | /wisdom/.msg/meta.json | No | 1. Extract session path and target scope from task description 2. Determine scan scope: explicit scope from task or `**/*` default 3. Get recent changed files: `git diff --name-only HEAD~5 2>/dev/null || echo ""` 4. Read .msg/meta.json for historical defect patterns (`defect_patterns`) 5. Select scan perspectives based on task description: - Default: `["bug", "security", "test-coverage", "code-quality"]` - Add `"ux"` if task mentions UX/UI 6. Assess complexity to determine scan strategy: | Complexity | Condition | Strategy | |------------|-----------|----------| | Low | < 5 changed files, no specific keywords | ACE search + Grep inline | | Medium | 5-15 files or specific perspective requested | CLI fan-out (3 core perspectives) | | High | > 15 files or full-project scan | CLI fan-out (all perspectives) | ## Phase 3: Multi-Perspective Scan **Low complexity**: Use `mcp__ace-tool__search_context` for quick pattern-based scan. **Medium/High complexity**: CLI fan-out -- one `ccw cli --mode analysis` per perspective: For each active perspective, build prompt: ``` PURPOSE: Scan code from perspective to discover potential issues TASK: Analyze code patterns for problems, identify anti-patterns, check for common issues MODE: analysis CONTEXT: @ EXPECTED: List of findings with severity (critical/high/medium/low), file:line references, description CONSTRAINTS: Focus on actionable findings only ``` Execute via: `ccw cli -p "" --tool gemini --mode analysis` After all perspectives complete: - Parse CLI outputs into structured findings - Deduplicate by file:line (merge perspectives for same location) - Compare against known defect patterns from .msg/meta.json - Rank by severity: critical > high > medium > low ## Phase 4: Result Aggregation 1. Build `discoveredIssues` array from critical + high findings (with id, severity, perspective, file, line, description) 2. Write scan results to `/scan/scan-results.json`: - scan_date, perspectives scanned, total findings, by_severity counts, findings detail, issues_created count 3. Update `/wisdom/.msg/meta.json`: merge `discovered_issues` field 4. Contribute to wisdom/issues.md if new patterns found