Meta Prompt Engineering
CheckedOptimizes prompts for AI models by analyzing and refining them—boosting response quality and accuracy for better results.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add lyndonkl/claude --skill meta-prompt-engineering -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
lyndonkl
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.
Automated safety checks
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 lyndonkl/claude at 4acc337d4d.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 4acc337d4d
- Scanned
- 4 files, 1,207 lines
About this skill
What it does
This skill allows you to craft more effective prompts for AI agents. It refines initial user requests, adding detail and structure to guide the agent towards a desired output. The skill is designed to improve the quality of responses by clarifying intent and providing context.
When to use it
- Generating creative content: Use it when needing help brainstorming or refining ideas for stories, poems, or scripts.
- Complex problem-solving: Employ this skill when tackling intricate tasks that require detailed instructions and specific constraints.
- Improving code generation: Leverage it to ensure the AI agent produces accurate and well-structured code by providing clear requirements.
- Data extraction & summarization: Use it to guide the agent in extracting precise information from text or summarizing lengthy documents with a focus on particular aspects.
Key capabilities
- Refines user prompts
- Adds detail and structure to requests
- Clarifies intent for AI agents
- Provides context for improved responses
Example prompts
- "Help me refine this prompt: 'Write a short story about a cat.'"
- "I want the agent to summarize this article, but focus on the economic impact. Can you help me structure my request?"
- “Can you improve this code generation prompt: ‘Write a Python function that sorts a list.’”
Tips & gotchas
The skill is most effective when given an initial prompt to work with; it’s not designed to generate prompts from scratch. Providing clear examples of the desired output can further enhance its refinement capabilities.