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Family Health Analyzer

Checked
huifer·vlatest·other·MIT

Analyzes family health data to identify potential risks and provide personalized insights for improved wellness management.

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 huifer/wellally-health --skill family-health-analyzer -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

huifer

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 huifer/claude-ally-health at f604350c84.

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

Scanned
2 files, 264 lines
Copies in repo
2 — all of them scanned
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 huifer-family-health-analyzer skill provides analysis of family health data. It can identify potential genetic risks and offer personalized recommendations based on provided information. The tool aims to assist users in understanding their family's health history and proactively addressing potential issues.

When to use it

  • Analyzing a newly discovered family medical record for potential hereditary conditions.
  • Preparing for a discussion with a healthcare professional about family health risks.
  • Generating a summary of family health information for future reference or sharing with relatives.
  • Exploring the implications of specific genetic markers found in family members.

Key capabilities

  • Genetic risk identification
  • Personalized recommendations
  • Family health data analysis
  • Health record summarization

Example prompts

  • "Analyze this family medical history and identify any potential genetic risks."
  • "Summarize the key health concerns present in my family's records."
  • "Based on this information, what preventative measures should I consider?"

Tips & gotchas

The accuracy of the analysis depends heavily on the completeness and correctness of the input data. Ensure you provide as much detail as possible for best results.