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Create Meta Prompts

Checked
glittercowboy·vlatest·ai-ml·MIT

Automatically generates optimized, layered prompts to guide AI models towards desired outputs and creative exploration.

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 glittercowboy/taches-cc-resources --skill create-meta-prompts -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

glittercowboy

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 glittercowboy/taches-cc-resources at 1757615b99.

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

Commit
1757615b99
Manifest
skills/create-meta-prompts/SKILL.md
Scanned
11 files, 3,008 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 generate structured meta-prompts that define the behavior, constraints, and output formats for subsequent tasks. It acts as a configuration layer, allowing agents to dynamically set up their own operational parameters before executing complex workflows.

When to use it

  • You need an agent to adopt a specific persona or tone without hard-coding instructions into every request.
  • You want to enforce strict output schemas (e.g., JSON, Markdown tables) across multiple iterations of a task.
  • You are building a multi-step workflow where the first step must define the rules for all following steps.
  • You need to dynamically adjust agent constraints based on user input before processing data.

Key capabilities

  • Generates self-contained prompt templates that dictate agent behavior.
  • Defines specific output formats and structural requirements.
  • Sets operational constraints and boundary conditions for task execution.
  • Creates reusable instruction sets for consistent agent performance.

Example prompts

  • "Create a meta-prompt that configures an agent to act as a senior Python developer, requiring all code snippets to include type hints and docstrings."
  • "Generate a meta-prompt that forces the output of any analysis task into a strict JSON format with specific nested keys for 'summary', 'data', and 'recommendations'."
  • "Build a meta-prompt that restricts an agent to only answering questions about a provided text file, refusing any external knowledge or hallucinations."

Tips & gotchas

Ensure the generated meta-prompt includes clear failure modes; without explicit constraints, agents may ignore the formatting rules they were asked to create. Test the output format immediately after generation to verify the agent adheres to the new structural requirements before running batch tasks.