--- name: schema-optimization-orchestrator description: | Multi-phase schema optimization workflow orchestrator. Creates session directories, spawns phase agents sequentially, validates outputs, aggregates results. Trigger: "run schema optimization", "optimize schema workflow", "execute schema phases" allowed-tools: Read, Write, Bash, Task version: 1.0.0 license: MIT author: Intent Solutions IO --- # Schema Optimization Orchestrator Runs a multi-phase schema optimization workflow with strict validation and evidence collection. ## Workflow Pattern This is a **test harness** pattern: - Creates isolated session directory per run - Spawns 5 phase agents sequentially - Each phase reads reference docs, runs scripts, writes reports - Validates JSON outputs and file artifacts - Aggregates final summary ## Inputs (JSON) ```json { "skill_dir": "\/absolute\/path\/to\/.claude\/skills\/schema-optimization", "input_folder": "\/path\/to\/bigquery\/export", "extraction_type": "bigquery_json", "session_dir_base": ".claude\/skills\/schema-optimization\/reports\/runs" } ``` Required: - **skill_dir**: Absolute path to this skill directory - **input_folder**: Path to data to analyze - **extraction_type**: Type of data extraction (e.g., "bigquery_json") Optional: - **session_dir_base**: Where to create run directories (default: reports\/runs) ## Orchestration Steps ### 1. Create Session Directory ```bash TIMESTAMP=$(date +%Y-%m-%d_%H%M%S) SESSION_DIR="${session_dir_base}\/${TIMESTAMP}" mkdir -p "${SESSION_DIR}" ``` ### 2. Run Phase 1: Initial Schema Analysis Spawn Phase 1 agent with: ```json { "skill_dir": "", "session_dir": "", "reference_path": "\/references\/01-phase-1.md", "input_folder": "", "extraction_type": "" } ``` Expected output: ```json { "status": "complete", "report_path": "\/01-initial-schema-analysis.md", "schema_summary": { "total_tables": 0, "total_fields": 0, "key_findings": [] } } ``` **Validation:** - JSON parse succeeds - `status` is "complete" - `report_path` file exists - `schema_summary` has required keys ### 3. Run Phase 2: Field Utilization Analysis Spawn Phase 2 agent with: ```json { "skill_dir": "", "session_dir": "", "reference_path": "\/references\/02-phase-2.md", "phase1_report_path": "", "input_folder": "" } ``` Expected output: ```json { "status": "complete", "report_path": "\/02-field-utilization-analysis.md", "utilization_summary": { "unused_fields": [], "low_utilization_fields": [], "recommendations": [] } } ``` ### 4. Run Phase 3: Impact Assessment Spawn Phase 3 agent with: ```json { "skill_dir": "", "session_dir": "", "reference_path": "\/references\/03-phase-3.md", "phase1_report_path": "", "phase2_report_path": "", "input_folder": "" } ``` Expected output: ```json { "status": "complete", "report_path": "\/03-impact-assessment.md", "impact_summary": { "high_risk_changes": [], "medium_risk_changes": [], "low_risk_changes": [], "estimated_savings": {} } } ``` ### 5. Run Phase 4: Verification with Script Spawn Phase 4 agent with: ```json { "skill_dir": "", "session_dir": "", "reference_path": "\/references\/04-phase-4-verify-with-script.md", "phase2_report_path": "", "phase3_report_path": "", "input_folder": "", "script_path": "\/scripts\/analyze_field_utilization.sh", "output_folder_path": "" } ``` Expected output: ```json { "status": "complete", "report_path": "\/04-field-utilization-verification.md", "verification_summary": { "files_analyzed": 0, "conclusions_confirmed": [], "conclusions_revised": [], "unexpected_findings": [], "revised_action_items": [] } } ``` ### 6. Run Phase 5: Final Recommendations Spawn Phase 5 agent with: ```json { "skill_dir": "", "session_dir": "", "reference_path": "\/references\/05-phase-5.md", "phase1_report_path": "", "phase2_report_path": "", "phase3_report_path": "", "phase4_report_path": "" } ``` Expected output: ```json { "status": "complete", "report_path": "\/05-final-recommendations.md", "recommendations_summary": { "priority_actions": [], "implementation_plan": [], "success_metrics": [] } } ``` ## Output (JSON Only) ```json { "status": "complete", "session_dir": "", "timestamp": "YYYY-MM-DD_HHMMSS", "phase_reports": { "phase1": "\/01-initial-schema-analysis.md", "phase2": "\/02-field-utilization-analysis.md", "phase3": "\/03-impact-assessment.md", "phase4": "\/04-field-utilization-verification.md", "phase5": "\/05-final-recommendations.md" }, "final_summary": { "total_tables": 0, "total_fields": 0, "unused_fields": 0, "optimization_opportunities": 0, "estimated_savings_pct": 0, "verification_status": "confirmed" } } ``` ## Error Handling If any phase fails: - Stop execution - Return error status with phase details - Preserve partial reports for debugging ```json { "status": "error", "failed_phase": 3, "error_message": "Phase 3 agent failed validation", "session_dir": "", "completed_phases": ["phase1", "phase2"] } ``` ## Validation Rules After each phase: 1. Parse returned JSON (fail if invalid) 2. Check `status` is "complete" (fail if not) 3. Verify `report_path` exists on disk (fail if not) 4. Validate phase-specific summary keys (fail if missing) ## Implementation Notes - Use Task tool to spawn phase agents - Pass exact file paths (no wildcards) - Session directory must be absolute path - All reports must be written before returning - No terminal output except final JSON ## Example Usage ``` User: "Run schema optimization on my BigQuery export" Claude: [Creates session directory] Claude: [Spawns Phase 1 agent] Claude: [Validates Phase 1 output] Claude: [Spawns Phase 2 agent with Phase 1 report] Claude: [... continues through Phase 5] Claude: [Returns final JSON summary] ``` ## Files Created Per Run ``` reports\/runs\/2025-01-15_143022\/ ├── 01-initial-schema-analysis.md ├── 02-field-utilization-analysis.md ├── 03-impact-assessment.md ├── 04-field-utilization-verification.md └── 05-final-recommendations.md ``` Each file is evidence of work completed.