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 vte-risk-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/vte-risk-assessment)<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/vte-risk-assessment"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/vte-risk-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/vte-risk-assessment"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/vte-risk-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 | $0.00112 | $0.02973 |
| Opus 5.5 | $0.00045 | $0.01189 |
| Sonnet 5.5 | $0.00022 | $0.00595 |
| Haiku 4.5 | $0.00011 | $0.00297 |
Grade A, and why
vte-risk-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 2mo 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 — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
VTE Risk Assessment
Overview
Calculate VTE risk scores from FHIR Patient, Condition, Observation, Procedure, and MedicationRequest resources. Supports Wells Criteria for DVT, Wells Criteria for PE, Revised Geneva Score for PE, and Caprini Score for surgical VTE prophylaxis. Generate prophylaxis and diagnostic recommendations based on risk stratification. Create a RiskAssessment FHIR resource documenting findings.
FHIR Resources Used
| Resource | Purpose | Key Fields |
|---|---|---|
| Patient | Age, gender | birthDate, gender |
| Condition | Active diagnoses, cancer, prior VTE, immobilization | code, clinicalStatus, onsetDateTime |
| Observation | Vitals (HR, SpO2), D-dimer, labs | code, valueQuantity, effectiveDateTime |
| Procedure | Recent surgeries, immobilization, central lines | code, status, performedDateTime |
| MedicationRequest | Hormonal therapy, anticoagulants, contraceptives | medicationCodeableConcept, status |
| RiskAssessment | Output: VTE risk scores | method, prediction, basis |
Instructions
Step 1: Retrieve Patient Demographics
Tool: fhir_read
resourceType: "Patient"
id: "[patient-id]"
Extract age and gender. Age >40 and >60 have incremental Caprini points.
Step 2: Retrieve Active and Historical Conditions
Tool: fhir_search
resourceType: "Condition"
queryParams: "patient=[patient-id]&clinical-status=active,recurrence,remission"
Key SNOMED codes for scoring:
- 128053003: Deep vein thrombosis
- 59282003: Pulmonary embolism
- 363346000: Malignant neoplasm (active cancer)
- 128599005: Thrombophilia (Factor V Leiden, protein C/S deficiency, antithrombin III deficiency, antiphospholipid syndrome)
- 40733004: Infectious disease (active infection)
- 22298006: Myocardial infarction (recent)
- 42343007: Congestive heart failure
- 84114007: Heart failure (NYHA class III-IV)
- 128613002: Inflammatory bowel disease
- 13645005: COPD
- 44054006: Diabetes mellitus type 2
- 414916001: Obesity
- 70691001: Varicose veins
- 309585006: Immobility
- 371128001: Leg swelling (current symptom for Wells DVT)
- 57676002: Hemoptysis (for Wells PE)
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.
- 2mo ago First seen · 304 lines · 112 tokens per session scan A 321a362669ef
vte-risk-assessment is a skill published in the GitHub repository langcare/langcare-mcp-fhir (71 stars, last pushed 6mo ago), licensed MIT. It adds 112 tokens to every session and 2,973 once invoked, about $0.0004 per session on Opus 5.5. 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.
vte-risk-assessment compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| vte-risk-assessmentlangcare/langcare-mcp-fhir | Skill | 71 | 6mo ago | MIT | A | 112 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |