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 chronic-pain-management-reviewgit 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/chronic-pain-management-review)<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/chronic-pain-management-review"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/chronic-pain-management-review/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/chronic-pain-management-review"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/chronic-pain-management-review.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 | $0.05072 |
| Opus 5 | $0.00056 | $0.02536 |
| Sonnet 5 | $0.00023 | $0.01014 |
| Haiku 4.5 | $0.00011 | $0.00507 |
Grade A, and why
chronic-pain-management-review 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 9d 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 — 438 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chronic Pain Management Review
Overview
Pull and analyze all pain-related clinical data for a comprehensive chronic pain management review. Retrieve pain-related Conditions, current analgesic MedicationRequests (opioid and non-opioid), pain score Observations over time, functional status assessments, and urine drug screen results. Calculate current daily morphine milligram equivalents (MME). Evaluate adherence to CDC 2022 opioid prescribing guidelines. Flag high-risk patterns: elevated MME, concurrent benzodiazepines, lack of multimodal approach, missing urine drug screens, absent naloxone prescription. Present structured review with risk mitigation recommendations.
FHIR Resources Used
| Resource | Purpose | Key Fields |
|---|---|---|
| Patient | Demographics, age | birthDate, gender |
| Condition | Pain diagnoses, comorbidities | code, clinicalStatus, onsetDateTime, bodySite |
| MedicationRequest | Analgesics, adjuvants, naloxone | medicationCodeableConcept, status, dosageInstruction, authoredOn |
| Observation | Pain scores, UDS, functional status | code, valueQuantity, effectiveDateTime, interpretation |
| Procedure | Pain interventions (injections, nerve blocks) | code, performedDateTime, status |
Instructions
Step 1: Retrieve Patient Demographics
Tool: fhir_read
resourceType: "Patient"
id: "[patient-id]"
Extract age, gender. Age is relevant for Beers criteria (>=65 years: avoid opioids as first-line per AGS).
Step 2: Pull Pain-Related Conditions
Tool: fhir_search
resourceType: "Condition"
queryParams: "patient=[patient-id]&code:below=22253000&clinical-status=active"
SNOMED 22253000 = Pain (finding). This captures chronic pain subtypes.
Also search for specific chronic pain conditions:
Tool: fhir_search
resourceType: "Condition"
queryParams: "patient=[patient-id]&code=82423001,279039007,203082005,431855005,73211009,724637000&clinical-status=active"
SNOMED codes:
- 82423001 = Chronic pain
- 279039007 = Low back pain
- 203082005 = Fibromyalgia
- 431855005 = Chronic widespread pain
- 73211009 = Diabetic neuropathy
- 724637000 = Complex regional pain syndrome
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.
- 9d ago First seen · 438 lines · 113 tokens per session scan A 4f314b3ee268
chronic-pain-management-review 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 5,072 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 2026-09-03.
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