What is opioid-risk-assessment?

An opioid safety review that calculates total daily morphine milligram equivalents, or MME, scores risk factors, and checks prescriptions against CDC guidance. MME converts different opioid doses into an approximate morphine-equivalent amount.

Use it to calculate opioid dose exposure, assess opioid-related risk, check benzodiazepine or gabapentinoid combinations, and identify missing naloxone prescribing.

It brings dose, prescription history, substance-use factors, and risky medicine combinations together to reveal situations needing closer review.

opioid-risk-assessment — Skill for Claude Code and Codex by langcare

Install

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.

Any agent

npx skills add langcare/langcare-mcp-fhir --skill opioid-risk-assessment

Clone the repo

git clone --depth 1 https://github.com/langcare/langcare-mcp-fhir

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/opioid-risk-assessment/github.svg)](https://agentmods.dev/skills/langcare/langcare-mcp-fhir/opioid-risk-assessment)

Your own site

<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/opioid-risk-assessment"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/opioid-risk-assessment/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/opioid-risk-assessment"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/opioid-risk-assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 108 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,114 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00108	$0.04114
Opus 5.5	$0.00043	$0.01646
Sonnet 5.5	$0.00022	$0.00823
Haiku 4.5	$0.00011	$0.00411

Measured 2mo ago against content hash 535501ac642c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

opioid-risk-assessment 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.

skills/core/medication-management/opioid-risk-assessment/SKILL.md · 370 lines

How it starts

The opening of the file, as written. The whole thing — 370 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Opioid Risk Assessment

Overview

Perform a comprehensive opioid risk assessment by pulling all active opioid prescriptions, calculating total daily morphine milligram equivalents (MME), applying Opioid Risk Tool (ORT) scoring criteria, and evaluating against CDC 2022 Clinical Practice Guideline thresholds. Flag MME >50 (caution), MME >90 (high risk), concurrent benzodiazepine use, concurrent gabapentinoid use, and absence of naloxone co-prescription. Include CAGE-AID screening questions for substance use risk assessment.

FHIR Resources Used

Resource	Purpose	Key Fields
MedicationRequest	Active opioid prescriptions with dosing	status, medicationCodeableConcept, dosageInstruction, dispenseRequest
MedicationStatement	Patient-reported opioid and concurrent substance use	status, medicationCodeableConcept, dosage
MedicationDispense	Opioid fill history for pattern analysis	status, medicationCodeableConcept, quantity, daysSupply, whenHandedOver
Patient	Demographics for ORT scoring (age, gender)	birthDate, gender
Condition	Psychiatric diagnoses, substance use history for ORT	code, clinicalStatus
Observation	Urine drug screen results, pain scores	code, valueCodeableConcept, valueQuantity

Instructions

Step 1: Retrieve Patient Demographics

Tool: fhir_read
resourceType: "Patient"
id: "[patient-id]"

Extract age and gender. Both are required for ORT scoring (scoring criteria differ by gender).

Step 2: Pull All Active Medications

Tool: fhir_search
resourceType: "MedicationRequest"
queryParams: "patient=[patient-id]&status=active&_count=100"

Classify each active medication:

Opioids: Identify by RxNorm code or drug name (see references/mme-conversion-table.md)
Benzodiazepines: alprazolam, clonazepam, diazepam, lorazepam, temazepam, triazolam, chlordiazepoxide, clorazepate, oxazepam, midazolam
Gabapentinoids: gabapentin, pregabalin
Z-drugs: zolpidem, zaleplon, eszopiclone
Muscle relaxants: carisoprodol, cyclobenzaprine, methocarbamol, tizanidine
Naloxone: Check if co-prescribed (nasal naloxone, injectable naloxone)

Read the full file on GitHub · 370 lines

Files

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.

Changes

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 · 370 lines · 108 tokens per session scan A 535501ac642c

Subscribe to this mod's changes

opioid-risk-assessment is a skill published in the GitHub repository langcare/langcare-mcp-fhir (71 stars, last pushed 6mo ago), licensed MIT. It adds 108 tokens to every session and 4,114 once invoked, about $0.0004 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 2026-09-03.

Scientific

opioid-risk-assessment next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
opioid-risk-assessmentlangcare/langcare-mcp-fhir	Skill	71	6mo ago	MIT	A	108	Claude Code, Codex
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exploratory-data-analysisK-Dense-AI/scientific-agent-skills	Skill	56k	4d ago	MIT	A	83	Claude Code
matlabK-Dense-AI/scientific-agent-skills	Skill	56k	4d ago	MIT	A	44	Claude Code
phylogeneticsK-Dense-AI/scientific-agent-skills	Skill	56k	4d ago	MIT	A	71	Claude Code, Codex
research-engineerdavila7/claude-code-templates	Skill	33k	yesterday	MIT	A	43	Claude Code, Codex
mapping-to-snomedmaziyarpanahi/openmed	Skill	5.8k	yesterday	Apache-2.0	A	205	Claude Code