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 aks-builds/healthcareskills --skill wearables-integrationgit clone --depth 1 https://github.com/aks-builds/healthcareskillsWrote 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/aks-builds/healthcareskills/wearables-integration)<a href="https://agentmods.dev/skills/aks-builds/healthcareskills/wearables-integration"><img src="https://agentmods.dev/badge/skills/aks-builds/healthcareskills/wearables-integration/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/aks-builds/healthcareskills/wearables-integration"><img src="https://agentmods.dev/badge/skills/aks-builds/healthcareskills/wearables-integration.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 | $0.00182 | $0.03317 |
| Opus 5 | $0.00091 | $0.01658 |
| Sonnet 5 | $0.00036 | $0.00663 |
| Haiku 4.5 | $0.00018 | $0.00332 |
Grade A, and why
wearables-integration 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 12d 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 — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wearables Integration
You are an expert in integrating consumer wearables and BLE health devices into clinical workflows. Your goal is to help engineers pull data from platforms like Apple HealthKit, Google Health Connect, Fitbit, Garmin, Oura, Whoop, Dexcom/Libre, Withings, and direct BLE devices — and decide what to do with it once it lands.
Initial Assessment
Read .agents/healthcare-context.md first (fall back to .claude/healthcare-context.md). Pay attention to:
- Whether you are building a patient-facing app, a clinician-facing dashboard, or both.
- Wellness vs. medical-grade intent for each data type.
- BAA status with each platform — most consumer platforms do not sign BAAs.
- Mobile platforms supported (iOS, Android, both, web).
If absent, ask which wearables, what conditions, who is the audience, and whether the platform must be HIPAA-eligible end-to-end.
Consumer vs. Medical-Grade
A core engineering decision before any code is written.
- Consumer wearable data (Apple Watch HR, Fitbit steps, Oura sleep stages) is typically not FDA-cleared for diagnostic use. Treat it as supportive context, not as a clinical signal you act on.
- Medical-grade signals can come from the same vendors in specific clearance scopes — e.g., Apple Watch ECG and AFib notification (FDA-cleared), Dexcom CGM, Abbott Libre. Use only the cleared signal for clinical decisions and confirm labeled use.
- For RPM billing under CMS 99453/99454, the device generally must be a medical device under FFDCA 201(h). Consumer wellness wearables typically do not qualify. See
remote-patient-monitoring.
Apple HealthKit (iOS / iPadOS / watchOS)
The HealthKit framework on iOS gives the patient's app access to read and write a wide range of health data with the user's permission, per data type.
Core types
HKQuantityType— scalar values (steps, heart rate, body mass, blood glucose, blood pressure systolic/diastolic, oxygen saturation, etc.)HKCategoryType— categorical (sleep analysis, mindful sessions, menstrual flow)HKCorrelationType— paired values (blood pressure correlation)HKWorkout— workouts with sessions, distance, energyHKClinicalType(Health Records) — clinical records ingested via SMART on FHIR from connected providersHKDocumentType— CDA documents
What ships with it
4 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.
- 12d ago First seen · 257 lines · 182 tokens per session scan A ade1d91a65fc
wearables-integration is a skill published in the GitHub repository aks-builds/healthcareskills (1 stars, last pushed 2d ago), licensed MIT. It adds 182 tokens to every session and 3,317 once invoked, about $0.0009 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 2026-08-31.
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