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Enhance Prompt

Official
google-labs-code·vlatest·ai-ml·Apache-2.0

This skill refines prompts for better AI responses, boosting marketing content generation quality and efficiency.

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 google-labs-code/stitch-skills --skill enhance-prompt -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

google-labs-code

Matched to the vendor's own GitHub organisation.

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 google-labs-code/stitch-skills at 0337446dad.

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

Commit
0337446dad
Manifest
plugins/stitch-utilities/skills/enhance-prompt/SKILL.md
Scanned
3 files, 337 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

The enhance-prompt skill helps users refine and improve their prompts for AI agents, making them more effective and clear. It provides suggestions to make prompts more specific, structured, or aligned with desired outcomes.

When to use it

  • You're struggling to get the right response from an AI agent due to vague phrasing.
  • You need to optimize a prompt for better results in content generation or task execution.
  • You want to ensure your prompt is well-structured and includes all necessary details.

Key capabilities

  • Suggests improvements to make prompts clearer and more actionable.
  • Helps identify missing context or ambiguity in the original prompt.
  • Offers alternative phrasings that may yield better results from AI agents.

Example prompts

  • "Can you help me rephrase this so it's easier for the AI to understand?"
  • "What would be a better way to ask for a marketing strategy outline?"
  • "How can I make this prompt more specific and effective?"

Tips & gotchas

  • Use this skill before sending complex or ambiguous prompts to ensure clarity.
  • While it improves prompts, it does not guarantee the AI agent will always produce perfect results—final output depends on the model's capabilities as well.