Llm Optimized Content
CheckedProvides LLMs guidance and assistance for building AI and machine learning applications.
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 guia-matthieu/clawfu-skills --skill llm-optimized-content -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
guia-matthieu
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 guia-matthieu/clawfu-skills at 4108f5c010.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 4108f5c010
- Scanned
- 1 file, 389 lines
About this skill
What it does
This skill optimizes text content for Large Language Models (LLMs). It restructures and formats input to improve LLM performance, specifically focusing on clarity and efficiency. The skill aims to reduce token usage while maintaining or improving the quality of generated output from LLMs.
When to use it
- Improving LLM response quality: Use when you notice an LLM struggling with complex instructions or producing suboptimal results.
- Reducing API costs: Optimize prompts and content to minimize token consumption, lowering expenses associated with LLM usage.
- Preparing training data: Format text datasets for more effective fine-tuning of LLMs.
- Simplifying complex documents: Restructure lengthy reports or articles into a format better suited for LLM processing.
Key capabilities
- Content restructuring
- Formatting optimization
- Token reduction
- LLM performance enhancement
Example prompts
- "Optimize this paragraph for use in an LLM prompt: [paragraph text]"
- "Restructure the following document to improve its clarity for a language model: [document text]"
- "Can you format this article so that it's more efficient for an LLM? [article text]"
Tips & gotchas
The effectiveness of this skill depends on the complexity and structure of the input content. While it aims to reduce token usage, always review the output to ensure the meaning is preserved.