Official agent skill

Postgresql Code Review

by github in github/awesome-copilot

PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards.

OfficialMITAuto-check passedDatabases

Install Postgresql Code Review

skills CLI
$ npx skills add github/awesome-copilot --skill postgresql-code-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install github/awesome-copilot postgresql-code-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/postgresql-code-review .claude/skills/postgresql-code-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
postgresql-code-review
GitHub stars
40k
Used in
2 other repos
Token cost
~1.8k tokens
SKILL.md length
361 words
Files
1
Skills in repo
417
Repo updated
First seen
Licence
MIT

At a glance

PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards.

  • Works in 7 steps: Data Type Optimization: Ensure… → Index Strategy: Review index types and… → JSONB Structure: Validate JSONB schema… → …
  • Tasks that involve Code review
  • SKILL.md covers 🎯 PostgreSQL-Specific Review…, 🔍 PostgreSQL-Specific…, 📊 PostgreSQL Extension Usage… and 🛡️ PostgreSQL Security Review, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Postgresql Code Review is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases, covering Code review and Database schema design. It works with PostgreSQL. The repository describes itself as: Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot. The licence is MIT.

When your agent uses it

  • Tasks that involve Code review
  • Tasks that involve Database schema design

Example prompts

  • “/postgresql-code-review”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Data Type Optimization: Ensure PostgreSQL-specific types are used appropriately
  2. Index Strategy: Review index types and ensure PostgreSQL-specific indexes are utilized
  3. JSONB Structure: Validate JSONB schema design and query patterns
  4. Function Quality: Review PL/pgSQL functions for efficiency and best practices
  5. Extension Usage: Verify appropriate use of PostgreSQL extensions
  6. Performance Features: Check utilization of PostgreSQL's advanced features
  7. Security Implementation: Review PostgreSQL-specific security features

What it can do on your machine

Read from SKILL.md and the folder at commit 727ff2e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are sql).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Postgresql Code Review loads about 1.8k tokens when it runs. Until then it costs about 78 tokens; SKILL.md has 361 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 361 words, ~1,847 tokens.

Download SKILL.mdSave it as .claude/skills/postgresql-code-review/SKILL.md (or your agent's skills folder).
name
postgresql-code-review
description
PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).

PostgreSQL Code Review Assistant

Expert PostgreSQL code review for ${selection} (or entire project if no selection). Focus on PostgreSQL-specific best practices, anti-patterns, and quality standards that are unique to PostgreSQL.

🎯 PostgreSQL-Specific Review Areas

JSONB Best Practices
sql
-- ❌ BAD: Inefficient JSONB usage
SELECT * FROM orders WHERE data->>'status' = 'shipped';  -- No index support

-- ✅ GOOD: Indexable JSONB queries
CREATE INDEX idx_orders_status ON orders USING gin((data->'status'));
SELECT * FROM orders WHERE data @> '{"status": "shipped"}';

-- ❌ BAD: Deep nesting without consideration
UPDATE orders SET data = data || '{"shipping":{"tracking":{"number":"123"}}}';

-- ✅ GOOD: Structured JSONB with validation
ALTER TABLE orders ADD CONSTRAINT valid_status 
CHECK (data->>'status' IN ('pending', 'shipped', 'delivered'));
Array Operations Review
sql
-- ❌ BAD: Inefficient array operations
SELECT * FROM products WHERE 'electronics' = ANY(categories);  -- No index

-- ✅ GOOD: GIN indexed array queries
CREATE INDEX idx_products_categories ON products USING gin(categories);
SELECT * FROM products WHERE categories @> ARRAY['electronics'];

-- ❌ BAD: Array concatenation in loops
-- This would be inefficient in a function/procedure

-- ✅ GOOD: Bulk array operations
UPDATE products SET categories = categories || ARRAY['new_category']
WHERE id IN (SELECT id FROM products WHERE condition);
PostgreSQL Schema Design Review
sql
-- ❌ BAD: Not using PostgreSQL features
CREATE TABLE users (
    id INTEGER,
    email VARCHAR(255),
    created_at TIMESTAMP
);

-- ✅ GOOD: PostgreSQL-optimized schema
CREATE TABLE users (
    id BIGSERIAL PRIMARY KEY,
    email CITEXT UNIQUE NOT NULL,  -- Case-insensitive email
    created_at TIMESTAMPTZ DEFAULT NOW(),
    metadata JSONB DEFAULT '{}',
    CONSTRAINT valid_email CHECK (email ~* '^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$')
);

-- Add JSONB GIN index for metadata queries
CREATE INDEX idx_users_metadata ON users USING gin(metadata);
Custom Types and Domains
sql
-- ❌ BAD: Using generic types for specific data
CREATE TABLE transactions (
    amount DECIMAL(10,2),
    currency VARCHAR(3),
    status VARCHAR(20)
);

-- ✅ GOOD: PostgreSQL custom types
CREATE TYPE currency_code AS ENUM ('USD', 'EUR', 'GBP', 'JPY');
CREATE TYPE transaction_status AS ENUM ('pending', 'completed', 'failed', 'cancelled');
CREATE DOMAIN positive_amount AS DECIMAL(10,2) CHECK (VALUE > 0);

CREATE TABLE transactions (
    amount positive_amount NOT NULL,
    currency currency_code NOT NULL,
    status transaction_status DEFAULT 'pending'
);

🔍 PostgreSQL-Specific Anti-Patterns

Performance Anti-Patterns
  • Avoiding PostgreSQL-specific indexes: Not using GIN/GiST for appropriate data types
  • Misusing JSONB: Treating JSONB like a simple string field
  • Ignoring array operators: Using inefficient array operations
  • Poor partition key selection: Not leveraging PostgreSQL partitioning effectively
Schema Design Issues
  • Not using ENUM types: Using VARCHAR for limited value sets
  • Ignoring constraints: Missing CHECK constraints for data validation
  • Wrong data types: Using VARCHAR instead of TEXT or CITEXT
  • Missing JSONB structure: Unstructured JSONB without validation
Function and Trigger Issues
sql
-- ❌ BAD: Inefficient trigger function
CREATE OR REPLACE FUNCTION update_modified_time()
RETURNS TRIGGER AS $$
BEGIN
    NEW.updated_at = NOW();  -- Should use TIMESTAMPTZ
    RETURN NEW;
END;
$$ LANGUAGE plpgsql;

-- ✅ GOOD: Optimized trigger function
CREATE OR REPLACE FUNCTION update_modified_time()
RETURNS TRIGGER AS $$
BEGIN
    NEW.updated_at = CURRENT_TIMESTAMP;
    RETURN NEW;
END;
$$ LANGUAGE plpgsql;

-- Set trigger to fire only when needed
CREATE TRIGGER update_modified_time_trigger
    BEFORE UPDATE ON table_name
    FOR EACH ROW
    WHEN (OLD.* IS DISTINCT FROM NEW.*)
    EXECUTE FUNCTION update_modified_time();

📊 PostgreSQL Extension Usage Review

Extension Best Practices
sql
-- ✅ Check if extension exists before creating
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";
CREATE EXTENSION IF NOT EXISTS "pgcrypto";
CREATE EXTENSION IF NOT EXISTS "pg_trgm";

-- ✅ Use extensions appropriately
-- UUID generation
SELECT uuid_generate_v4();

-- Password hashing
SELECT crypt('password', gen_salt('bf'));

-- Fuzzy text matching
SELECT word_similarity('postgres', 'postgre');

🛡️ PostgreSQL Security Review

Row Level Security (RLS)
sql
-- ✅ GOOD: Implementing RLS
ALTER TABLE sensitive_data ENABLE ROW LEVEL SECURITY;

CREATE POLICY user_data_policy ON sensitive_data
    FOR ALL TO application_role
    USING (user_id = current_setting('app.current_user_id')::INTEGER);
Privilege Management
sql
-- ❌ BAD: Overly broad permissions
GRANT ALL PRIVILEGES ON ALL TABLES IN SCHEMA public TO app_user;

-- ✅ GOOD: Granular permissions
GRANT SELECT, INSERT, UPDATE ON specific_table TO app_user;
GRANT USAGE ON SEQUENCE specific_table_id_seq TO app_user;

🎯 PostgreSQL Code Quality Checklist

Schema Design
  • Using appropriate PostgreSQL data types (CITEXT, JSONB, arrays)
  • Leveraging ENUM types for constrained values
  • Implementing proper CHECK constraints
  • Using TIMESTAMPTZ instead of TIMESTAMP
  • Defining custom domains for reusable constraints
Performance Considerations
  • Appropriate index types (GIN for JSONB/arrays, GiST for ranges)
  • JSONB queries using containment operators (@>, ?)
  • Array operations using PostgreSQL-specific operators
  • Proper use of window functions and CTEs
  • Efficient use of PostgreSQL-specific functions
Show full SKILL.md (149 more words)Show less
PostgreSQL Features Utilization
  • Using extensions where appropriate
  • Implementing stored procedures in PL/pgSQL when beneficial
  • Leveraging PostgreSQL's advanced SQL features
  • Using PostgreSQL-specific optimization techniques
  • Implementing proper error handling in functions
Security and Compliance
  • Row Level Security (RLS) implementation where needed
  • Proper role and privilege management
  • Using PostgreSQL's built-in encryption functions
  • Implementing audit trails with PostgreSQL features

📝 PostgreSQL-Specific Review Guidelines

  1. Data Type Optimization: Ensure PostgreSQL-specific types are used appropriately
  2. Index Strategy: Review index types and ensure PostgreSQL-specific indexes are utilized
  3. JSONB Structure: Validate JSONB schema design and query patterns
  4. Function Quality: Review PL/pgSQL functions for efficiency and best practices
  5. Extension Usage: Verify appropriate use of PostgreSQL extensions
  6. Performance Features: Check utilization of PostgreSQL's advanced features
  7. Security Implementation: Review PostgreSQL-specific security features

Focus on PostgreSQL's unique capabilities and ensure the code leverages what makes PostgreSQL special rather than treating it as a generic SQL database.

© github, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/postgresql-code-review of github/awesome-copilot.

Open the folder on GitHubat commit 727ff2e

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in github/awesome-copilot, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Postgresql Code Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Postgresql Code Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Postgresql Code Review this skillgithub/awesome-copilot40k2 repos~1.8kAutomated safety check: PassMIT
SQL Code Reviewtotvs/engpro-advpl-tlpp-skills141—~3.5kAutomated safety check: PassMIT
Supabase Postgres Best Practicessupabase/agent-skills2.7k24 repos~808Automated safety check: PassMIT
Saleor Django Migration Rulessaleor/saleor23k—~1.6kAutomated safety check: PassBSD-3-Clause
Schema Explorationtimescale/pg-aiguide1.9k—~1.1kAutomated safety check: PassApache-2.0
Database DesignMoizIbnYousaf/ai-agent-skills1.1k1 repos~1.2kAutomated safety check: PassMIT

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Works with

Questions about Postgresql Code Review

What does Postgresql Code Review do?

PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Postgresql Code Review is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards.

When should I use Postgresql Code Review?

Postgresql Code Review fits situations like: tasks that involve Code review; tasks that involve Database schema design.

How do I install Postgresql Code Review in Claude Code?

Run `npx skills add github/awesome-copilot --skill postgresql-code-review -a claude-code`. Or copy the skill folder (skills/postgresql-code-review in github/awesome-copilot) into .claude/skills/postgresql-code-review in your project. Claude Code loads it when a task matches its description.

How do I install Postgresql Code Review in Codex?

Run `npx skills add github/awesome-copilot --skill postgresql-code-review -a codex`. Or copy the skill folder (skills/postgresql-code-review in github/awesome-copilot) into .agents/skills/postgresql-code-review in your project. Codex loads it when a task matches its description.

Can I use Postgresql Code Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add github/awesome-copilot --skill postgresql-code-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/postgresql-code-review, .gemini/skills/postgresql-code-review, .github/skills/postgresql-code-review and .opencode/skills/postgresql-code-review in your project.

What does Postgresql Code Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Postgresql Code Review is instructions for the agent only.

Does Postgresql Code Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Postgresql Code Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Postgresql Code Review use?

Postgresql Code Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Postgresql Code Review use?

About 1.8k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Postgresql Code Review?

Skills that share tags, products or a category with Postgresql Code Review: SQL Code Review (totvs/engpro-advpl-tlpp-skills, 141 stars), Supabase Postgres Best Practices (supabase/agent-skills, 2.7k stars), Saleor Django Migration Rules (saleor/saleor, 23k stars) and Schema Exploration (timescale/pg-aiguide, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Postgresql Code Review?

github (a GitHub organization, an official publisher) maintains it in github/awesome-copilot, which has 39,748 GitHub stars. The repository holds 417 skills in this directory. The repository was last updated on October 7, 2026.

Source: github/awesome-copilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.