health-skillz: A Claude Skill for connecting to and analyzing personal health records via SMART on FHIR

by jmandel · Claude Skill · ★ 82

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install health-skillz

git clone https://github.com/jmandel/health-skillz

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 73/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentsclaude-skillsehrehr-dataepichealthhealthcaresmart-on-fhir-fhir

Quick Facts

Stars82
Forks8
LanguageTypeScript
CategoryClaude Skill
Quality Score73/100
Open Issues4
Last Updated2026-06-08
Created2026-01-12
Platformsclaude-code, node
Est. Tokens~887k

About health-skillz

Health Skillz Health Skillz helps people collect SMART on FHIR records from patient portals, review/export them locally, and optionally share them with AI using end-to-end encrypted upload. Documentation Design and architecture: Environment/runbook notes: This README intentionally stays high-level. API contracts, data structures, security model, and protocol details are documented in .

Compatible Skills

These tools work well together with health-skillz for enhanced workflows:

  • starknet-agentic — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (52%)
  • openpaw — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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