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 follow-up-task-generatorgit 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/follow-up-task-generator)<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/follow-up-task-generator"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/follow-up-task-generator/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/follow-up-task-generator"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/follow-up-task-generator.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 | $0.00094 | $0.04228 |
| Opus 5 | $0.00047 | $0.02114 |
| Sonnet 5 | $0.00019 | $0.00846 |
| Haiku 4.5 | $0.00009 | $0.00423 |
Grade A, and why
follow-up-task-generator 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 — 385 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Follow-Up Task Generator
Overview
Analyze a patient's recent clinical data -- encounters, condition changes, lab results, procedures, and medication changes -- to identify required follow-up actions. Generate FHIR Task resources for each follow-up item with appropriate urgency classification (urgent, soon, routine), responsible party assignment, and due dates based on clinical standards.
FHIR Resources Used
| Resource | Purpose | Key Fields |
|---|---|---|
| Task | Generated follow-up tasks | status, priority, code, for, owner, requester, restriction.period, description, focus, reasonReference |
| Encounter | Recent visits triggering follow-up | type, period, reasonCode, class |
| Condition | Active/new conditions requiring monitoring | code, clinicalStatus, onsetDateTime, category |
| Observation | Lab results requiring follow-up | code, valueQuantity, interpretation, effectiveDateTime, referenceRange |
| Procedure | Recent procedures requiring post-procedure follow-up | code, performedDateTime, status |
| MedicationRequest | Medication changes requiring monitoring | medicationCodeableConcept, status, authoredOn, dosageInstruction |
| DiagnosticReport | Imaging/pathology requiring follow-up | code, conclusion, status |
| Practitioner | Provider assignment | name, identifier, specialty |
| ServiceRequest | Existing pending orders | status, code, intent |
Instructions
Step 1: Retrieve Recent Encounter
Tool: fhir_search
resourceType: "Encounter"
queryParams: "patient=[patient-id]&_sort=-date&_count=3"
Identify the encounter(s) triggering follow-up generation. Extract: encounter type, date, reason, provider.
Step 2: Retrieve Abnormal Lab Results
Tool: fhir_search
resourceType: "Observation"
queryParams: "patient=[patient-id]&category=laboratory&date=ge=[30-days-ago]&_sort=-date"
Identify results requiring follow-up by checking:
interpretationfield: "H" (high), "L" (low), "HH" (critical high), "LL" (critical low), "A" (abnormal)- Values outside
referenceRange - Critical values requiring immediate action (see
references/task-prioritization.md) - Results that are preliminary or need confirmation
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 · 385 lines · 94 tokens per session scan A 9c314ea0a037
follow-up-task-generator is a skill published in the GitHub repository langcare/langcare-mcp-fhir (55 stars, last pushed 5mo ago), licensed MIT. It adds 94 tokens to every session and 4,228 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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