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-tasksgit 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-tasks)<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/follow-up-tasks"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/follow-up-tasks/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-tasks"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/follow-up-tasks.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 | $0.00069 | $0.00652 |
| Opus 5.5 | $0.00028 | $0.00261 |
| Sonnet 5.5 | $0.00014 | $0.00130 |
| Haiku 4.5 | $0.00007 | $0.00065 |
Grade A, and why
langcare-follow-up-tasks 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Follow-Up Task Generator
When to Use This Skill
Use when a clinician needs to generate actionable follow-up tasks after an encounter, ensuring nothing falls through the cracks.
Clinical Workflow
- Use
fhir_searchto pull the recent Encounter and its associated resources - Use
fhir_searchto identify pending ServiceRequest resources (labs ordered but not resulted, imaging ordered, referrals sent) - Use
fhir_searchto identify new MedicationRequest resources requiring follow-up monitoring (new statin -> recheck LFTs in 6 weeks; new ACEi -> recheck BMP in 2 weeks) - Use
fhir_searchto identify Condition resources with time-based follow-up needs - Generate Task resources for each follow-up item with: description, owner, due date, priority, and status
- Use
fhir_createto create Task resources in FHIR
FHIR Resources
- Encounter -- Visit context and associated resources
- ServiceRequest -- Pending orders to track
- MedicationRequest -- New medications requiring monitoring
- Condition -- Conditions requiring follow-up
- Task -- Output: follow-up task items with owner, due date, priority
FHIR Query Examples
Pull Pending Orders
fhir_search(resourceType="ServiceRequest", queryParams="patient=[patient-id]&status=active&_sort=-authored&_count=50")
Create Follow-Up Task
fhir_create(resourceType="Task", resource={"resourceType":"Task","status":"requested","intent":"order","priority":"routine","description":"[task description]","for":{"reference":"Patient/[patient-id]"},"executionPeriod":{"end":"[due-date]"}})
Clinical Guidelines
- AHRQ guidelines for results management and follow-up
- Test results management: all ordered tests must have a documented review and action
- Medication monitoring timelines per drug-specific guidelines
Interpretation Guide
- Categorize tasks by type: pending results, medication monitoring, referral tracking, screening due, patient callback
- Assign priority: urgent (results expected to change management), routine (standard monitoring), low (administrative)
- Include specific due dates based on clinical guidelines (e.g., recheck potassium 1 week after starting ACEi, recheck A1c 3 months after medication change)
- Flag overdue tasks from prior encounters that were never completed
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 · 59 lines · 69 tokens per session scan A 52a3ff6dc417
langcare-follow-up-tasks is a skill published in the GitHub repository langcare/langcare-mcp-fhir (71 stars, last pushed 6mo ago), licensed MIT. It adds 69 tokens to every session and 652 once invoked, about $0.0003 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.
langcare-follow-up-tasks compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| langcare-follow-up-taskslangcare/langcare-mcp-fhir | Skill | 71 | 6mo ago | MIT | A | 69 | 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 |