Prompt Optimizer
CheckedOptimizes AI prompts for better results by refining phrasing and structure, boosting your model's performance and efficiency.
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 chujianyun/skills --skill prompt-optimizer -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
chujianyun
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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 chujianyun/skills at 62e7c89b94.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 62e7c89b94
- Manifest
- skills/prompt-optimizer/SKILL.md
- Scanned
- 60 files, 6,698 lines
About this skill
What it does
This Prompt Optimizer skill helps users refine their AI prompts to achieve better results. It analyzes user input (a prompt, task description, or vague idea) and selects an appropriate prompting framework based on complexity and domain. The skill then generates a more clear and executable prompt tailored to the specific task, improving model performance and efficiency.
When to use it
- When you have a draft prompt that isn't producing desired results.
- When you need help translating a vague idea into a well-structured AI prompt.
- For tasks requiring more complex prompting strategies (e.g., marketing content creation, decision analysis).
- To ensure your prompts are optimized for specific domains like education or marketing.
Key capabilities
- Prompt Analysis: Evaluates existing prompts and task descriptions to identify areas for improvement.
- Framework Selection: Matches user scenarios with suitable prompting frameworks based on complexity (simple, medium, complex) and domain (marketing, decision analysis, education).
- Ambiguity Clarification: Asks clarifying questions about the target audience, constraints, and desired output format if necessary.
- Prompt Generation: Generates optimized prompts using selected frameworks.
- Framework Library: Utilizes a library of prompting frameworks (e.g., APE, RACE, CRISPE) to guide prompt creation.
Example prompts
- "Can you optimize this prompt: 'Write a short story about a cat'?"
- "I need help creating a prompt for generating marketing content for social media."
- "I have an idea for a new product but I don’t know how to turn it into a prompt for AI."
Tips & gotchas
- The skill won't automatically apply complex frameworks to simple prompts. It prioritizes clarity and efficiency.
- If you only want minor adjustments, the skill may not be necessary as it tends to generate more structured prompts.
- Be prepared to answer clarifying questions about your task’s goals, audience, and desired output format if they are unclear initially.