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 pneumonia-severity-assessmentgit 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/pneumonia-severity-assessment)<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/pneumonia-severity-assessment"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/pneumonia-severity-assessment/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/pneumonia-severity-assessment"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/pneumonia-severity-assessment.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 | $0.00113 | $0.04384 |
| Opus 5 | $0.00056 | $0.02192 |
| Sonnet 5 | $0.00023 | $0.00877 |
| Haiku 4.5 | $0.00011 | $0.00438 |
Grade A, and why
pneumonia-severity-assessment 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 13d 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 — 405 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pneumonia Severity Assessment
Overview
Calculate pneumonia severity scores from FHIR Patient, Observation, and Condition resources using CURB-65, PSI/PORT Score (Pneumonia Severity Index), and A-DROP criteria. Differentiate community-acquired pneumonia (CAP) from hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP). Generate disposition recommendations (outpatient, observation, inpatient, ICU) and empiric antibiotic guidance based on severity level and guidelines. Create a ClinicalImpression resource documenting findings.
FHIR Resources Used
| Resource | Purpose | Key Fields |
|---|---|---|
| Patient | Age, gender, nursing home residence | birthDate, gender, address |
| Condition | Comorbidities, pneumonia type, pleural effusion | code, clinicalStatus, onsetDateTime |
| Observation | Vitals (BP, HR, RR, temp, SpO2), labs (BUN, glucose, Na, Hct, PaO2, pH) | code, valueQuantity, effectiveDateTime |
| Encounter | Admission source, current encounter type | class, period, hospitalization |
| MedicationRequest | Current antibiotics, immunosuppressants | medicationCodeableConcept, status |
| ClinicalImpression | Output: severity assessment | status, description, finding |
Instructions
Step 1: Retrieve Patient Demographics
Tool: fhir_read
resourceType: "Patient"
id: "[patient-id]"
Extract age (exact years), gender (male = additional PSI points). Check address for nursing home/long-term care facility (affects CAP vs HCAP classification).
Step 2: Determine CAP vs HAP/VAP
Tool: fhir_search
resourceType: "Encounter"
queryParams: "patient=[patient-id]&status=in-progress"
Classification logic:
- CAP: Pneumonia onset before or within 48 hours of hospital admission. Includes nursing home patients (previously "HCAP" -- per 2019 ATS/IDSA guidelines, HCAP category eliminated; treat as CAP unless HAP/VAP risk factors present).
- HAP: Pneumonia onset >=48 hours after hospital admission, not intubated at time of onset.
- VAP: Pneumonia onset >=48 hours after endotracheal intubation.
What ships with it
2 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.
- 13d ago First seen · 405 lines · 113 tokens per session scan A abf24df957d7
pneumonia-severity-assessment is a skill published in the GitHub repository langcare/langcare-mcp-fhir (55 stars, last pushed 5mo ago), licensed MIT. It adds 113 tokens to every session and 4,384 once invoked, about $0.0006 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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