Postgresql Optimization

PostgreSQL Optimization Workflow

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/postgresql-optimization from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

PostgreSQL Optimization Workflow

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Optimization Checklist, Quality Gates, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Optimizing slow PostgreSQL queries
• Designing indexing strategies
• Analyzing database performance
• Tuning PostgreSQL configuration
• Managing production databases
• Use when the request clearly matches the imported source intent: PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. database-optimizer - Database optimization
2. postgres-best-practices - PostgreSQL best practices
3. Check database version
4. Review configuration
5. Analyze slow queries
6. Check resource usage
7. Identify bottlenecks

Imported Workflow Notes

Imported: Workflow Phases

Phase 1: Performance Assessment

Skills to Invoke

• database-optimizer - Database optimization
• postgres-best-practices - PostgreSQL best practices

Actions

1. Check database version
2. Review configuration
3. Analyze slow queries
4. Check resource usage
5. Identify bottlenecks

Copy-Paste Prompts

Use @database-optimizer to assess PostgreSQL performance

Phase 2: Query Analysis

Skills to Invoke

• sql-optimization-patterns - SQL optimization
• postgres-best-practices - PostgreSQL patterns

Actions

1. Run EXPLAIN ANALYZE
2. Identify scan types
3. Check join strategies
4. Analyze execution time
5. Find optimization opportunities

Copy-Paste Prompts

Use @sql-optimization-patterns to analyze and optimize queries

Phase 3: Indexing Strategy

Skills to Invoke

• database-design - Index design
• postgresql - PostgreSQL indexing

Actions

1. Identify missing indexes
2. Create B-tree indexes
3. Add composite indexes
4. Consider partial indexes
5. Review index usage

Copy-Paste Prompts

Use @database-design to design PostgreSQL indexing strategy

Phase 4: Query Optimization

Skills to Invoke

• sql-optimization-patterns - Query tuning
• sql-pro - SQL expertise

Actions

1. Rewrite inefficient queries
2. Optimize joins
3. Add CTEs where helpful
4. Implement pagination
5. Test improvements

Copy-Paste Prompts

Use @sql-optimization-patterns to optimize SQL queries

Phase 5: Configuration Tuning

Skills to Invoke

• postgres-best-practices - Configuration
• database-admin - Database administration

Actions

1. Tune shared_buffers
2. Configure work_mem
3. Set effective_cache_size
4. Adjust checkpoint settings
5. Configure autovacuum

Copy-Paste Prompts

Use @postgres-best-practices to tune PostgreSQL configuration

Phase 6: Maintenance

Skills to Invoke

• database-admin - Database maintenance
• postgresql - PostgreSQL maintenance

Actions

1. Schedule VACUUM
2. Run ANALYZE
3. Check table bloat
4. Monitor autovacuum
5. Review statistics

Copy-Paste Prompts

Use @database-admin to schedule PostgreSQL maintenance

Phase 7: Monitoring

Skills to Invoke

• grafana-dashboards - Monitoring dashboards
• prometheus-configuration - Metrics collection

Actions

1. Set up monitoring
2. Create dashboards
3. Configure alerts
4. Track key metrics
5. Review trends

Copy-Paste Prompts

Use @grafana-dashboards to create PostgreSQL monitoring

Imported: Related Workflow Bundles

• database - Database operations
• cloud-devops - Infrastructure
• performance-optimization - Performance

Imported: Overview

Specialized workflow for PostgreSQL database optimization including query tuning, indexing strategies, performance analysis, vacuum management, and production database administration.

Imported: Optimization Checklist

• Slow queries identified
• Indexes optimized
• Configuration tuned
• Maintenance scheduled
• Monitoring active
• Performance improved

Examples

Example 1: Ask for the upstream workflow directly

Use @postgresql-optimization to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @postgresql-optimization against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @postgresql-optimization for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @postgresql-optimization using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/postgresql-optimization, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Quality Gates

• Query performance improved
• Indexes effective
• Configuration optimized
• Maintenance automated
• Monitoring in place

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.