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Database Optimizer

Checked
claudchereji·vlatest·database

Optimizes Claudchereji databases for speed and efficiency through automated indexing, query analysis, and schema adjustments.

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 claudchereji/visualverses --skill database-optimizer -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

claudchereji

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 claudchereji/visualverses at 5971350ec1.

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

Commit
5971350ec1
Manifest
.opencode/skills/database-optimizer/SKILL.md
Scanned
1 file, 281 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 optimizes databases to improve performance and efficiency. It analyzes database schemas, queries, and indexes to identify bottlenecks and suggests improvements. The tool aims to reduce query execution times and overall resource consumption for database operations.

When to use it

  • You're experiencing slow query response times in an application.
  • Your database server is consistently running at high CPU utilization.
  • You need to optimize a large database for improved reporting performance.
  • You are migrating a database and want to ensure optimal efficiency on the new platform.

Key capabilities

  • Database schema analysis
  • Query optimization suggestions
  • Index recommendations
  • Performance bottleneck identification

Example prompts

  • "Analyze my PostgreSQL database and suggest ways to improve query performance."
  • "Identify slow queries in my MySQL database."
  • “Recommend indexes for a table with frequent joins.”

Tips & gotchas

The skill's effectiveness depends on providing accurate database connection details. It is recommended to test optimizations in a staging environment before applying them to production databases.