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Schema optimization

Skill jeremylongshore/claude-code-plugins-plus-skills/workspace/lab/schema-optimization

425 plugins, 2,810 skills, 200 agents for Claude Code. Open-source marketplace at tonsofskills.com with the ccpi CLI package manager.

Install
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill schema-optimization

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What its author says it does

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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"

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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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)

{
  "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

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:

{
  "skill_dir": "<skill_dir>",
  "session_dir": "<SESSION_DIR>",
  "reference_path": "<skill_dir>/references/01-phase-1.md",
  "input_folder": "<input_folder>",
  "extraction_type": "<extraction_type>"
}

Expected output:

{
  "status": "complete",
  "report_path": "<SESSION_DIR>/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:

{
  "skill_dir": "<skill_dir>",
  "session_dir": "<SESSION_DIR>",
  "reference_path": "<skill_dir>/references/02-phase-2.md",
  "phase1_report_path": "<phase1_report_path>",
  "input_folder": "<input_folder>"
}

Expected output:

{
  "status": "complete",
  "report_path": "<SESSION_DIR>/02-field-utilization-analysis.md",
  "utilization_summary": {
    "unused_fields": [],
    "low_utilization_fields": [],
    "recommendations": []
  }
}

4. Run Phase 3: Impact Assessment

Spawn Phase 3 agent with:

{
  "skill_dir": "<skill_dir>",
  "session_dir": "<SESSION_DIR>",
  "reference_path": "<skill_dir>/references/03-phase-3.md",
  "phase1_report_path": "<phase1_report_path>",
  "phase2_report_path": "<phase2_report_path>",
  "input_folder": "<input_folder>"
}

Expected output:

{
  "status": "complete",
  "report_path": "<SESSION_DIR>/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:

{
  "skill_dir": "<skill_dir>",
  "session_dir": "<SESSION_DIR>",
  "reference_path": "<skill_dir>/references/04-phase-4-verify-with-script.md",
  "phase2_report_path": "<phase2_report_path>",
  "phase3_report_path": "<phase3_report_path>",
  "input_folder": "<input_folder>",
  "script_path": "<skill_dir>/scripts/analyze_field_utilization.sh",
  "output_folder_path": "<input_folder>"
}

Expected output:

{
  "status": "complete",
  "report_path": "<SESSION_DIR>/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:

{
  "skill_dir": "<skill_dir>",
  "session_dir": "<SESSION_DIR>",
  "reference_path": "<skill_dir>/references/05-phase-5.md",
  "phase1_report_path": "<phase1_report_path>",
  "phase2_report_path": "<phase2_report_path>",
  "phase3_report_path": "<phase3_report_path>",
  "phase4_report_path": "<phase4_report_path>"
}

Expected output:

{
  "status": "complete",
  "report_path": "<SESSION_DIR>/05-final-recommendations.md",
  "recommendations_summary": {
    "priority_actions": [],
    "implementation_plan": [],
    "success_metrics": []
  }
}

Output (JSON Only)

{
  "status": "complete",
  "session_dir": "<SESSION_DIR>",
  "timestamp": "YYYY-MM-DD_HHMMSS",
  "phase_reports": {
    "phase1": "<SESSION_DIR>/01-initial-schema-analysis.md",
    "phase2": "<SESSION_DIR>/02-field-utilization-analysis.md",
    "phase3": "<SESSION_DIR>/03-impact-assessment.md",
    "phase4": "<SESSION_DIR>/04-field-utilization-verification.md",
    "phase5": "<SESSION_DIR>/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
{
  "status": "error",
  "failed_phase": 3,
  "error_message": "Phase 3 agent failed validation",
  "session_dir": "<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.

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