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Claude Skill

Checked
feiskyer·vlatest·ai-ml·MIT

The Claude Skill allows you to seamlessly integrate Claude’s powerful language model into your workflows for enhanced content generation and analysis.

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 feiskyer/openclaw-kubernetes --skill claude-skill -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

feiskyer

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 feiskyer/openclaw-kubernetes at d9ca7edfcd.

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

Scanned
2 files, 630 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 integrates with Claude, an AI assistant developed by Anthropic. It allows agents to leverage Claude's natural language processing capabilities, including text generation, summarization, and question answering. The skill provides a streamlined interface for interacting with Claude within the agent workflow.

When to use it

  • Content Creation: Generate marketing copy, blog posts, or creative writing pieces based on specific prompts.
  • Summarization: Quickly condense lengthy documents or articles into concise summaries.
  • Question Answering: Retrieve information from a knowledge base by posing questions in natural language.
  • Code Generation/Explanation: Request code snippets in various programming languages, or have existing code explained.

Key capabilities

  • Integration with Claude AI assistant
  • Text generation
  • Summarization of text
  • Question answering
  • Code generation and explanation

Example prompts

  • "Write a short poem about the ocean."
  • "Summarize this article: [paste article content here]"
  • "Explain how to implement a binary search in Python."

Tips & gotchas

Claude has context window limitations; very long inputs may be truncated. Consider breaking down large tasks into smaller, more manageable steps for optimal results.