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-paingit 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)<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/chronic-pain"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/chronic-pain/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"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/chronic-pain.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 | $0.00072 | $0.00901 |
| Opus 5.5 | $0.00029 | $0.00360 |
| Sonnet 5.5 | $0.00014 | $0.00180 |
| Haiku 4.5 | $0.00007 | $0.00090 |
Grade A, and why
langcare-chronic-pain 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chronic Pain Management Review
When to Use This Skill
Use when a clinician needs a comprehensive evaluation of a chronic pain patient's current management including pain scores, medication regimen, functional status, and guideline compliance.
Clinical Workflow
- Use
fhir_readto retrieve Patient demographics - Use
fhir_searchto pull Condition resources for pain diagnoses (chronic pain, neuropathy, fibromyalgia, low back pain, osteoarthritis) - Use
fhir_searchto pull Observation resources for pain scores (LOINC 72514-3) and functional assessments over time - Use
fhir_searchto pull active MedicationRequest for current pain regimen: opioids, NSAIDs, acetaminophen, gabapentinoids, antidepressants (duloxetine, TCAs), topicals, muscle relaxants - If opioids present, calculate total daily MME and apply CDC 2022 thresholds (see references/cdc-pain-guidelines.md)
- Use
fhir_searchto pull Procedure resources for interventional pain procedures (injections, nerve blocks, spinal cord stimulation) - Assess multimodal therapy: physical therapy referrals, CBT/psychology referrals, complementary medicine
- Present comprehensive pain management dashboard with pain trend, current regimen, MME (if applicable), functional status, and recommended optimizations
FHIR Resources
- Condition -- Pain diagnoses with ICD-10/SNOMED codes
- Observation -- Pain scores (LOINC 72514-3), functional assessments, UDS
- MedicationRequest -- Current pain medications
- Procedure -- Interventional procedures, physical therapy
- ServiceRequest -- Referrals (pain clinic, PT, psychology, complementary)
FHIR Query Examples
Pull Pain Scores Over Time
fhir_search(resourceType="Observation", queryParams="patient=[patient-id]&code=72514-3&_sort=date&_count=20")
Pull Pain Diagnoses
fhir_search(resourceType="Condition", queryParams="patient=[patient-id]&clinical-status=active")
Pull Pain Medications
fhir_search(resourceType="MedicationRequest", queryParams="patient=[patient-id]&status=active&_count=100")
What ships with it
1 file 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 · 68 lines · 72 tokens per session scan A 28dd42daca26
langcare-chronic-pain is a skill published in the GitHub repository langcare/langcare-mcp-fhir (71 stars, last pushed 6mo ago), licensed MIT. It adds 72 tokens to every session and 901 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-chronic-pain compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| langcare-chronic-painlangcare/langcare-mcp-fhir | Skill | 71 | 6mo ago | MIT | A | 72 | 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 |