Analyzes PostgreSQL query execution plans using EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) and the pg_stat_statements extension. Identifies sequential scans, nested loop inefficiencies, and index recommendations for slow queries.
Scanned 6/8/2026
Install via CLI
openskills install agentskillexchange/skills---
name: "PostgreSQL Query Plan Diagnostics"
slug: "postgresql-query-plan-diagnostics-wave48"
description: "Analyzes PostgreSQL query execution plans using EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) and the pg_stat_statements extension. Identifies sequential scans, nested loop inefficiencies, and index recommendations for slow queries."
github_stars: 13127
verification: "security_reviewed"
source: "https://github.com/brianc/node-postgres"
category: "Runbooks & Diagnostics"
framework: "Claude Code"
tool_ecosystem:
github_repo: "brianc/node-postgres"
github_stars: 13127
npm_package: "pg"
npm_weekly_downloads: 23169914
---
# PostgreSQL Query Plan Diagnostics
Analyzes PostgreSQL query execution plans using EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) and the pg_stat_statements extension. Identifies sequential scans, nested loop inefficiencies, and index recommendations for slow queries.
## Installation
Use the upstream install or setup path that matches your environment:
- npm install pg
- From your workspace root run yarn and then yarn lerna bootstrap
- Run yarn test to run all the tests.
Requirements and caveats from upstream:
- # node-postgres
- 
- Non-blocking PostgreSQL client for Node.js. Pure JavaScript and optional native libpq bindings.
Basic usage or getting-started notes:
- ## Documentation
- Each package in this repo should have its own readme more focused on how to develop/contribute. For overall documentation on the project and the related modules managed by this repo please see:
- ### Features
- Source: https://github.com/brianc/node-postgres
- Extracted from upstream docs: https://raw.githubusercontent.com/brianc/node-postgres/HEAD/README.md
## Source
- [Agent Skill Exchange](https://agentskillexchange.com/skills/postgresql-query-plan-diagnostics-wave48/)
No comments yet. Be the first to comment!
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Interview, source-challenge, verify, save, and ADR-gate fuzzy coding requests into Codex-ready implementation specs. Use when a feature, bugfix, refactor, migration, repo-wide change, or architecture task needs user-verified requirements, source-backed decisions, durable architecture decisions, acceptance criteria, validation commands, rollout notes, saved spec/ADR files, and a Codex execution prompt. Do not use when already fully specified or when the user wants direct implementation now.
Use when a repo needs CodeGraph plus ast-grep for Codex MCP setup, exploration, impact analysis, structural search, or safe refactor planning.