Medical Research Agent Skills is a library of agent instructions for medical and biomedical research, covering evidence analysis, study protocol design, data analysis, and academic writing. Researchers use it to guide compatible coding agents through common scientific workflows. The catalogue contains many of the library's skills and commands.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aipoch/medical-research-skills --skill hipaa-compliance-auditorgit clone --depth 1 https://github.com/aipoch/medical-research-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aipoch/medical-research-skills/hipaa-compliance-auditor)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/hipaa-compliance-auditor"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/hipaa-compliance-auditor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/hipaa-compliance-auditor"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/hipaa-compliance-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.02689 |
| Opus 5 | $0.00029 | $0.01345 |
| Sonnet 5 | $0.00012 | $0.00538 |
| Haiku 4.5 | $0.00006 | $0.00269 |
Grade A, and why
hipaa-compliance-auditor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HIPAA Compliance Auditor
A clinical-grade PII/PHI detection and de-identification tool for healthcare text data.
Quick Check
Use this command to verify that the packaged script entry point can be parsed before deeper execution.
python -m py_compile scripts/main.py
Audit-Ready Commands
Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.
python -m py_compile scripts/main.py
python scripts/main.py --help
python scripts/main.py --text "Audit validation sample with explicit methods, findings, and conclusion."
When to Use
- Use this skill when the task needs A clinical-grade PII/PHI detection and de-identification tool for healthcare text data.
- Use this skill for academic writing tasks that require explicit assumptions, bounded scope, and a reproducible output format.
- Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.
When NOT to Use
- Do NOT use for DICOM image de-identification (use dicom-anonymizer skill)
- Do NOT use for general data anonymization of structured databases (use dedicated tools)
- Do NOT use as a legal compliance certification — this tool assists but does NOT replace human HIPAA review
Workflow
Step 1: Provide Input Text
Provide clinical text in one of two ways:
- File input:
python scripts/main.py --input patient_text.txt --output deidentified.txt - Direct text:
python scripts/main.py --text "Patient John Doe, SSN 123-45-6789..." --audit-log audit.json
If neither input provided: Request the text or file path from the user. Do not proceed without input.
Step 2: Configure Detection Parameters
--confidence 0.7(default): Minimum confidence threshold (0.0-1.0). Lower = more detections but more false positives.--preserve-structure true(default): Maintain document formatting after redaction--custom-patterns <path>: Optional custom regex patterns JSON for institution-specific identifiers
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 312 lines · 58 tokens per session scan A 243ce6e64bb3
hipaa-compliance-auditor is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 2,689 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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