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Ruleset Optimization

Checked
ilude·vlatest·other

Automatically refines complex rule sets to improve efficiency and accuracy within ilude's AI agents.

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 ilude/claude-code-config --skill ruleset-optimization -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

ilude

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 ilude/claude-code-config at 3587466021.

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

Commit
3587466021
Manifest
skills/ruleset-optimization/SKILL.md
Scanned
1 file, 127 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 Claude's code generation rulesets. It refines existing rules to improve output quality and adherence to specific guidelines, focusing on clarity and efficiency. The tool aims to enhance Claude’s ability to produce more reliable and predictable code based on provided instructions.

When to use it

  • Improving Code Quality: When generated code consistently misses requirements or contains errors.
  • Enforcing Coding Standards: To ensure Claude adheres to specific coding style guides or best practices.
  • Reducing Hallucinations: When Claude generates incorrect or fabricated information within the code.
  • Customizing Output: Tailoring Claude's responses for particular project needs and constraints.

Key capabilities

  • Ruleset refinement
  • Output quality improvement
  • Adherence to coding guidelines
  • Error reduction

Example prompts

  • "Optimize this ruleset to prioritize code comments."
  • "Refine the existing ruleset for Python code generation, focusing on PEP 8 compliance."
  • "Improve this ruleset so that generated code avoids using deprecated libraries."

Tips & gotchas

The effectiveness of this skill depends heavily on the quality and specificity of the initial ruleset. Providing clear examples of desired behavior alongside the existing ruleset will yield better results.