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Prompt Optimize

Checked
labring·vlatest·ai-ml

Labring's prompt-optimize refines your prompts to maximize AI model output quality and efficiency through iterative 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 labring/fastgpt --skill prompt-optimize -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

labring

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 labring/fastgpt at e0e826bbf4.

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

Commit
e0e826bbf4
Manifest
.agents/skills/core/ai/prompt_optimize/SKILL.md
Scanned
1 file, 231 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 helps refine and improve prompts given to AI agents. It analyzes existing prompts, suggests modifications to enhance clarity and effectiveness, and can iterate on prompts to achieve desired outcomes from the AI model. The goal is to maximize the quality of responses by optimizing the initial input.

When to use it

  • You're getting inconsistent or unsatisfactory results from an AI agent.
  • You want to ensure your instructions to an AI are as clear and precise as possible.
  • You’re experimenting with different prompting techniques to improve performance on a specific task.
  • You need help structuring complex requests for the AI model.

Key capabilities

  • Prompt analysis
  • Suggestion generation
  • Iterative refinement
  • Clarity enhancement

Example prompts

  • "Optimize this prompt: 'Write a short story about a cat.'"
  • "Can you improve this instruction for generating marketing copy? 'Create an ad for our new product.'"
  • "Analyze and suggest improvements to this prompt: 'Summarize the following article...'"

Tips & gotchas

The effectiveness of this skill depends on the quality of the initial prompt; a poorly written prompt will be difficult to optimize. Consider providing context or examples alongside your prompts for better results.