Skip to content
TrustedSkillsbeta
Back to all skills

Database Performance Debugging

Checked
aj-geddes·vlatest·testing·MIT

Helps with database, performance optimization, debugging as part of testing, debugging, and quality assurance workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add aj-geddes/useful-ai-prompts --skill database-performance-debugging -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

aj-geddes

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned aj-geddes/useful-ai-prompts at 3f5182cfd7.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
3f5182cfd7
Manifest
skills/database-performance-debugging/SKILL.md
Scanned
7 files, 320 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to analyze database query execution plans and identify performance bottlenecks within SQL workloads. It helps diagnose slow queries by examining index usage, join strategies, and resource consumption patterns directly from the source content context.

When to use it

  • Diagnosing why specific reports or dashboards are loading slower than expected.
  • Identifying missing indexes that cause full table scans on large datasets.
  • Optimizing complex joins that result in high CPU or memory usage.
  • Troubleshooting latency spikes caused by inefficient query structures.

Key capabilities

  • Analyzes raw execution plans to reveal hidden inefficiencies.
  • Detects suboptimal index utilization and suggests improvements.
  • Evaluates join order and strategy for better performance.
  • Highlights queries with excessive resource consumption.

Example prompts

  • "Analyze this EXPLAIN output and tell me why the query is scanning the full table instead of using an index."
  • "Review these slow query logs and identify the top three bottlenecks based on execution time and I/O wait."
  • "Suggest an optimized version of this SQL join that reduces memory usage by avoiding a hash spill."

Tips & gotchas

Ensure you provide full execution plan details (like EXPLAIN ANALYZE) for accurate diagnosis, as partial logs may miss critical resource metrics. This skill is most effective when paired with actual query performance data rather than generic descriptions of slow behavior.