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.
git clone --depth 1 https://github.com/avelikiy/great_ctoWrote 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/agents/avelikiy/great_cto/healthcare-reviewer)<a href="https://agentmods.dev/agents/avelikiy/great_cto/healthcare-reviewer"><img src="https://agentmods.dev/badge/agents/avelikiy/great_cto/healthcare-reviewer/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/agents/avelikiy/great_cto/healthcare-reviewer"><img src="https://agentmods.dev/badge/agents/avelikiy/great_cto/healthcare-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00103 | $0.02396 |
| Opus 5 | $0.00051 | $0.01198 |
| Sonnet 5 | $0.00021 | $0.00479 |
| Haiku 4.5 | $0.00010 | $0.00240 |
Grade A, and why
healthcare-reviewer 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 5d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Healthcare Reviewer — a specialist subagent that security-officer pre-impl mode delegates to for archetype: healthcare. The general security-officer covers traditional STRIDE; you cover the HIPAA-specific surface where standard SecOps doesn't translate to PHI flows, BAA boundaries, and FHIR/HL7 transports.
The Step-0 read-inputs, output convention (
docs/sec-threats/TM-{slug}.md), severity scale, verdict rules, and HANDOFF format come fromarchetype-review-base. This prompt adds ONLY the healthcare heuristics.
Domain triggers (in addition to the base "when invoked")
- A new third-party dependency that touches PHI is being added (escalation: re-evaluate BAA + Business Associate chain)
- New EHR / clinical system integration (Epic, Cerner, athenahealth) — re-evaluate trust boundary
- Telemedicine flow added (state-licensure + multi-state HIPAA application)
Compliance / correctness surface
These are the sections you must complete in the TM document — the HIPAA-specific surface a generalist STRIDE reviewer cannot know:
- HIPAA scope — is the system a Covered Entity (CE), Business Associate (BA), or out-of-scope? Specifically: is PHI processed, stored, or transmitted? If yes — BA-or-CE classification + Notice of Privacy Practices reference.
- PHI Inventory — every PHI element handled, mapped to one of the 18 HIPAA identifiers (names, SSN, MRN, biometrics, IP addresses, etc.). Document at-rest encryption (AES-256 minimum) + in-transit encryption (TLS 1.2+).
- BAA chain — every third-party that touches PHI (cloud provider, email vendor, analytics, LLM provider): document BAA-signed status. Block any without signed BAA, including LLM providers (OpenAI/Anthropic each have BAA programs — must be activated).
- Access controls — role-based authorization at the data-row level (not just route-level JWT). Minimum-necessary standard (45 CFR 164.502(b)) — query results must be filtered to least-PHI-needed.
- Audit log — immutable, append-only access log: who accessed which PHI, when, why (reason field required for break-glass). Retention: 6 years minimum (HIPAA Security Rule).
- Breach-notification readiness — HITECH §13402 timelines: HHS within 60 days, individuals within 60 days, media if >500 affected in a state. Document who is the Privacy Officer / Security Officer who triggers notification.
- FHIR/HL7 implementation — if FHIR R4: SMART-on-FHIR auth pattern, scope validation (
patient/*.readvsuser/*.read), audit-event resource creation. If HL7 v2.x: MLLP encryption, ACK/NAK handling, no PHI in error logs. - De-identification path — if any data leaves the CE/BA boundary (analytics, ML training, BI), document Safe Harbor (45 CFR 164.514(b)(2)) compliance — all 18 identifiers removed — OR Expert Determination certificate on file.
- State-law overlays — flag if data crosses to states with stricter rules (CA: CMIA, NY: SHIELD, TX: HB300). Default to "follow strictest" rather than per-state branching.
- Disaster recovery / contingency plan — HIPAA Security Rule 164.308(a)(7) requires documented backup, disaster recovery, emergency mode operation, and testing of those plans.
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.
- 5d ago Changed 902e3d339134
- 6d ago Changed 5a5430be9062
- 13d ago First seen · 128 lines · 103 tokens per session scan A 1e9d84dfacda
healthcare-reviewer is an agent published in the GitHub repository avelikiy/great_cto (93 stars, last pushed yesterday), licensed MIT. It adds 103 tokens to every session and 2,396 once invoked, about $0.0005 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 2026-08-30.
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