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Epidemiologist Analyst

Checked
rysweet·vlatest·data

This Epidemiologist Analyst skill analyzes data to identify disease patterns and trends, aiding in proactive public health responses and informed decision-making.

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 rysweet/amplihack --skill epidemiologist-analyst -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

rysweet

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 rysweet/amplihack at 84424457d5.

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

Commit
84424457d5
Manifest
.claude/skills/epidemiologist-analyst/SKILL.md
Scanned
8 files, 5,552 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

This skill enables AI agents to perform advanced epidemiological analysis, transforming raw health data into actionable insights regarding disease spread and public health trends. It supports complex statistical modeling to predict outbreaks and evaluate intervention strategies effectively.

When to use it

  • Analyzing time-series data to forecast infection rates during a potential pandemic.
  • Evaluating the efficacy of specific public health interventions like vaccination campaigns or lockdowns.
  • Identifying high-risk geographic clusters based on demographic and environmental variables.
  • Generating reports that summarize complex statistical findings for non-expert stakeholders.

Key capabilities

  • Statistical modeling and simulation of disease transmission dynamics.
  • Processing and interpreting large-scale epidemiological datasets.
  • Risk assessment and prediction of future outbreak scenarios.
  • Visualization of trends to support evidence-based decision-making.

Example prompts

  • "Run a statistical model to predict the spread of a hypothetical virus in urban areas with high population density."
  • "Analyze this dataset of recent case reports to identify emerging hotspots and suggest containment measures."
  • "Evaluate the impact of mask mandates on transmission rates using historical data from similar outbreaks."

Tips & gotchas

Ensure input data is clean, anonymized, and statistically significant before running models to avoid skewed predictions. This skill requires a foundational understanding of epidemiological concepts to correctly interpret the generated analysis and recommendations.