Domain Ml

Name: Domain Ml
Author: zhanghandong

Checked

zhanghandong·vlatest·ai-ml

Analyzes domain-specific text data using machine learning to extract insights and inform decision-making processes.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Run this in your project

terminal

$ npx skills add actionbook/rust-skills --skill domain-ml -a claude-code

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 28 Sept 2026

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/domain-ml/SKILL.md
Scanned: 1 file, 170 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 domain-ml skill enables AI agents to perform machine learning tasks within a specific domain, such as processing structured data or applying models tailored for niche applications. It supports model training, inference, and evaluation using domain-specific datasets.

When to use it

To train custom models on specialized datasets like medical records or financial transactions.
For deploying lightweight ML models in environments with limited computational resources.
When integrating AI capabilities into domain-specific tools or workflows that require precision.

Key capabilities

Model training and fine-tuning for specific domains
Inference using optimized, domain-aware algorithms
Integration with structured data formats like CSV or JSON

Example prompts

"Train a model to classify customer feedback as positive or negative."
"Predict equipment failure based on sensor data from industrial machinery."
"Generate insights from a dataset of medical diagnoses."

Tips & gotchas

Ensure your domain-specific datasets are clean and well-labeled for best results.
This skill may require additional libraries or dependencies not included by default.