--- name: schema-optimization-orchestrator-b39ef0dc20dd 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. --- Source attribution: jeremylongshore Original project: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/ab85a061f7bcc039dac13ee193de7a4cd4388571/workspace/lab/schema-optimization/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2025 Jeremy Longshore Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: jeremylongshore Original project: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/ab85a061f7bcc039dac13ee193de7a4cd4388571/workspace/lab/schema-optimization/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Development & Engineering Roles: Data Analyst, Data Scientist, ML / AI Engineer Specialties: API, Database Tools: Bash, Task Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 9d9698e9db7ccc9bd74c71d1b7cf0308d626810821a9cecef06b072ab52fdf87