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 lab-result-interpretergit 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/lab-result-interpreter)<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/lab-result-interpreter"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/lab-result-interpreter/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/lab-result-interpreter"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/lab-result-interpreter.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 | $0.00090 | $0.03662 |
| Opus 5 | $0.00045 | $0.01831 |
| Sonnet 5 | $0.00018 | $0.00732 |
| Haiku 4.5 | $0.00009 | $0.00366 |
Grade A, and why
lab-result-interpreter 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 — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lab Result Interpreter
Overview
Pull laboratory Observation resources for a patient. Organize by panel type (CBC, BMP, CMP, liver, lipids, thyroid, coagulation, urinalysis). Flag abnormal values using the interpretation field and referenceRange. Calculate delta checks against prior results to detect clinically significant changes. Identify critical values requiring immediate action. Correlate abnormal patterns with differential diagnoses. Present results in structured clinical format with trend analysis.
FHIR Resources Used
| Resource | Purpose | Key Fields |
|---|---|---|
| Observation | Lab results | code, valueQuantity, interpretation, referenceRange, effectiveDateTime, status, component |
| Condition | Clinical correlation | code, clinicalStatus, onsetDateTime |
| MedicationStatement | Drug-lab correlation | medicationCodeableConcept, status, effectivePeriod |
| Patient | Age/sex for reference ranges | birthDate, gender |
Instructions
Step 1: Retrieve Patient Demographics
Tool: fhir_read
resourceType: "Patient"
id: "[patient-id]"
Extract birthDate (calculate age) and gender. These determine reference range selection -- many analytes have age- and sex-specific ranges.
Step 2: Pull Recent Laboratory Observations
Tool: fhir_search
resourceType: "Observation"
queryParams: "patient=[patient-id]&category=laboratory&date=ge[target-date]&_sort=-date&_count=200"
If user requests a specific panel, narrow with LOINC codes:
- CBC panel:
code=58410-2 - BMP:
code=51990-0 - CMP:
code=24323-8 - Liver panel:
code=24325-3 - Lipid panel:
code=57698-3 - Thyroid panel:
code=3016-3,3026-2,3024-7
Default date range: ge[30-days-ago] unless user specifies otherwise.
Step 3: Organize Results by Panel Category
Group Observations by code.coding LOINC into:
- CBC: WBC (26464-8), RBC (789-8), Hemoglobin (718-7), Hematocrit (4544-3), MCV (787-2), MCH (785-6), MCHC (786-4), RDW (788-0), Platelets (777-3), MPV (32623-1), Differential (WBC subtypes)
- BMP/CMP: Sodium (2951-2), Potassium (2823-3), Chloride (2075-0), CO2 (1963-8), BUN (3094-0), Creatinine (2160-0), Glucose (2345-7), Calcium (17861-6), Albumin (1751-7), Total Protein (2885-2), ALP (6768-6), ALT (1742-6), AST (1920-8), Bilirubin Total (1975-2)
- Liver: ALT (1742-6), AST (1920-8), ALP (6768-6), GGT (2324-2), Bilirubin Total (1975-2), Bilirubin Direct (1968-7), Albumin (1751-7)
- Lipids: Total Cholesterol (2093-3), LDL (18262-6), HDL (2085-9), Triglycerides (2571-8), VLDL (13457-7)
- Thyroid: TSH (3016-3), Free T4 (3024-7), Free T3 (3026-2)
- Coagulation: PT (5902-2), INR (6301-6), aPTT (3173-2), Fibrinogen (3255-7), D-dimer (48066-5)
- Urinalysis: specific gravity (5811-5), pH (5803-2), protein (5804-0), glucose (5792-7), ketones (5797-6), blood (5794-3)
What ships with it
3 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 · 277 lines · 90 tokens per session scan A 83c5609b2aa7
lab-result-interpreter is a skill published in the GitHub repository langcare/langcare-mcp-fhir (55 stars, last pushed 5mo ago), licensed MIT. It adds 90 tokens to every session and 3,662 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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