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 langcare/langcare-mcp-fhir --skill chronic-disease-registriesgit clone --depth 1 https://github.com/langcare/langcare-mcp-fhirWrote 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/langcare/langcare-mcp-fhir/chronic-disease-registries)<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/chronic-disease-registries"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/chronic-disease-registries/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/langcare/langcare-mcp-fhir/chronic-disease-registries"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/chronic-disease-registries.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 | $0.00076 | $0.00718 |
| Opus 5 | $0.00038 | $0.00359 |
| Sonnet 5 | $0.00015 | $0.00144 |
| Haiku 4.5 | $0.00008 | $0.00072 |
Grade A, and why
langcare-chronic-disease-registries 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chronic Disease Registry Query
When to Use This Skill
Use when a clinician or care manager needs a disease-specific population report with severity stratification, control metrics, and patients needing escalation.
Clinical Workflow
- Use
fhir_searchto pull all patients with the target Condition (e.g., diabetes, HTN, CHF) active - For each patient, use
fhir_searchto pull key outcome Observations (A1c for diabetes, BP for HTN, EF for CHF, FEV1 for COPD, eGFR for CKD) - Stratify by severity/control: well-controlled, moderately controlled, poorly controlled, unknown (no recent data)
- Use
fhir_searchto pull active MedicationRequest for each patient to assess therapy appropriateness - Identify patients needing intervention: above target despite therapy, no recent monitoring, on suboptimal regimen
- Present registry report with population counts, severity distribution, and actionable patient lists
FHIR Resources
- Condition -- Registry population identification
- Patient -- Demographics for stratification
- Observation -- Disease-specific outcome measures
- MedicationRequest -- Current therapy assessment
FHIR Query Examples
Pull Diabetes Registry
fhir_search(resourceType="Condition", queryParams="code=http://snomed.info/sct|44054006&clinical-status=active&_count=500")
Pull A1c Values for Registry Patients
fhir_search(resourceType="Observation", queryParams="code=http://loinc.org|4548-4&date=ge[6-months-ago]&_sort=-date&_count=500")
Clinical Guidelines
- PCMH population management standards
- Disease-specific guidelines (ADA for diabetes, AHA/ACC for CHF, GOLD for COPD, KDIGO for CKD)
- CMS Chronic Care Management requirements
Interpretation Guide
- Registry dashboard format: total patients, severity tiers (by control metric), therapy distribution, patients needing action
- For diabetes registry: stratify by A1c (<7, 7-8, 8-9, >9, no recent A1c); report statin and ACEi/ARB rates
- For HTN registry: stratify by last BP (<130/80, 130-140/80-90, >140/90, no recent BP); report medication class distribution
- For CHF registry: stratify by EF (HFrEF <40%, HFmrEF 40-49%, HFpEF >=50%); report GDMT utilization (ACEi/ARB/ARNI, beta-blocker, MRA, SGLT2i)
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 · 58 lines · 76 tokens per session scan A 00124d74a9a3
langcare-chronic-disease-registries is a skill published in the GitHub repository langcare/langcare-mcp-fhir (55 stars, last pushed 5mo ago), licensed MIT. It adds 76 tokens to every session and 718 once invoked, about $0.0004 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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