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M09 Domain

Checked
zhanghandong·vlatest·other

M09 Domain provides targeted information retrieval by focusing on specific domains, streamlining research and boosting efficiency.

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 actionbook/rust-skills --skill m09-domain -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

zhanghandong

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 zhanghandong/rust-skills at 5c40d3ad78.

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

Commit
5c40d3ad78
Manifest
skills/m09-domain/SKILL.md
Scanned
1 file, 165 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

The m09-domain skill enables AI agents to identify and work with domain-specific information, such as extracting relevant data from text or understanding context within a particular field. It is particularly useful for tasks that require parsing structured content or recognizing entities related to specific domains.

When to use it

  • When analyzing technical documents or reports in specialized fields like engineering or medicine.
  • When extracting key terms or concepts from unstructured text for categorization.
  • When preparing data for domain-specific AI models that require contextual understanding.

Key capabilities

  • Domain entity recognition
  • Contextual information extraction
  • Structured content parsing

Example prompts

  • "Extract all medical conditions mentioned in this patient report."
  • "Identify the key engineering terms used in this technical manual."
  • "Parse and categorize the financial data from this document by domain."

Tips & gotchas

  • Ensure that the input text is relevant to the target domain for accurate results.
  • This skill may require additional training or fine-tuning for highly specialized fields not covered by default models.