MR
Mayur Rathi
@mayurrathi
⭐ 40.7k GitHub stars

Postgresql Optimization

Postgresql Optimization is an code AI skill with a core value of PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management. It helps developers solve real-world problems in the code domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

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

Last verified on: 2026-07-08

Quick Facts

Category code
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 40.7k
Last Verified 2026-07-08
Risk Level Low
mkdir -p ./skills/postgresql-optimization && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/postgresql-optimization/SKILL.md -o ./skills/postgresql-optimization/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# PostgreSQL Development Assistant


Expert PostgreSQL guidance for ${selection} (or entire project if no selection). Focus on PostgreSQL-specific features, optimization patterns, and advanced capabilities.


� PostgreSQL-Specific Features


JSONB Operations

sql
-- Advanced JSONB queries
CREATE TABLE events (
    id SERIAL PRIMARY KEY,
    data JSONB NOT NULL,
    created_at TIMESTAMPTZ DEFAULT NOW()
);

-- GIN index for JSONB performance
CREATE INDEX idx_events_data_gin ON events USING gin(data);

-- JSONB containment and path queries
SELECT * FROM events 
WHERE data @> '{"type": "login"}'
  AND data #>> '{user,role}' = 'admin';

-- JSONB aggregation
SELECT jsonb_agg(data) FROM events WHERE data ? 'user_id';

Array Operations

sql
-- PostgreSQL arrays
CREATE TABLE posts (
    id SERIAL PRIMARY KEY,
    tags TEXT[],
    categories INTEGER[]
);

-- Array queries and operations
SELECT * FROM posts WHERE 'postgresql' = ANY(tags);
SELECT * FROM posts WHERE tags && ARRAY['database', 'sql'];
SELECT * FROM posts WHERE array_length(tags, 1) > 3;

-- Array aggregation
SELECT array_agg(DISTINCT category) FROM posts, unnest(categories) as category;

Window Functions & Analytics

sql
-- Advanced window functions
SELECT 
    product_id,
    sale_date,
    amount,
    -- Running totals
    SUM(amount) OVER (PARTITION BY product_id ORDER BY sale_date) as running_total,
    -- Moving averages
    AVG(amount) OVER (PARTITION BY product_id ORDER BY sale_date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) as moving_avg,
    -- Rankings
    DENSE_RANK() OVER (PARTITION BY EXTRACT(month FROM sale_date) ORDER BY amount DESC) as monthly_rank,
    -- Lag/Lead for comparisons
    LAG(amount, 1) OVER (PARTITION BY product_id ORDER BY sale_date) as prev_amount
FROM sales;

Full-Text Search

sql
-- PostgreSQL full-text search
CREATE TABLE documents (
    id SERIAL PRIMARY KEY,
    title TEXT,
    content TEXT,
    search_vector tsvector
);

-- Update search vector
UPDATE documents 
SET search_vector = to_tsvector('english', title || ' ' || content);

-- GIN index for search performance
CREATE INDEX idx_documents_search ON documents USING gin(search_vector);

-- Search queries
SELECT * FROM documents 
WHERE search_vector @@ plainto_tsquery('english', 'postgresql database');

-- Ranking results
SELECT *, ts_rank(search_vector, plainto_tsquery('postgresql')) as rank
FROM documents 
WHERE search_vector @@ plainto_tsquery('postgresql')
ORDER BY rank DESC;

� PostgreSQL Performance Tuning


Query Optimization

sql
-- EXPLAIN ANALYZE for performance analysis
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) 
SELECT u.name, COUNT(o.id) as order_count
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
WHERE u.created_at > '2024-01-01'::date
GROUP BY u.id, u.name;

-- Identify slow queries from pg_stat_statements
SELECT query, calls, total_time, mean_time, rows,
       100.0 * shared_blks_hit / nullif(shared_blks_hit + shared_blks_read, 0) AS hit_percent
FROM pg_stat_statements 
ORDER BY total_time DESC 
LIMIT 10;

Index Strategies

sql
-- Composite indexes for multi-column queries
CREATE INDEX idx_orders_user_date ON orders(user_id, order_date);

-- Partial indexes for filtered queries
CREATE INDEX idx_active_users ON users(created_at) WHERE status = 'active';

-- Expression indexes for computed values
CREATE INDEX idx_users_lower_email ON users(lower(email));

-- Covering indexes to avoid table lookups
CREATE INDEX idx_orders_covering ON orders(user_id, status) INCLUDE (total, created_at);

Connection & Memory Management

sql
-- Check connection usage
SELECT count(*) as connections, state 
FROM pg_stat_activity 
GROUP BY state;

-- Monitor memory usage
SELECT name, setting, unit 
FROM pg_settings 
WHERE name IN ('shared_buffers', 'work_mem', 'maintenance_work_mem');

�️ PostgreSQL Advanced Data Types


Custom Types & Domains

sql
-- Create custom types
CREATE TYPE address_type AS (
    street TEX

🎯 Best For

  • Claude users
  • Software engineers
  • Development teams
  • Tech leads

💡 Use Cases

  • Code quality improvement
  • Best practice enforcement

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Postgresql Optimization to Your Work

    Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.

  4. 4

    Review and Refine

    Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.

❓ Frequently Asked Questions

Is Postgresql Optimization compatible with Cursor and VS Code?

Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.

Do I need specific dependencies for Postgresql Optimization?

Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.

How do I install Postgresql Optimization?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/postgresql-optimization/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Skipping validation

Always test AI-generated code changes, even for simple refactors.

Missing dependency updates

Check if the skill requires updated dependencies or new packages.

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