langcare-beers-criteria

langcare-beers-criteria is a skill for Claude Code, Codex from langcare/langcare-mcp-fhir. It costs 78 tokens per session (697 once invoked), scanned A, original, MIT.

A medication review for adults aged 65 and older based on the 2023 AGS Beers Criteria. These criteria identify medicines that may be unsafe, need caution, or require adjustment in older adults.

In plain words
What is it for?
Finding medicines to avoid, medicines needing caution or renal dose adjustment, drug-disease conflicts, and drug interactions, with evidence details and safer alternatives.
Why use it?
It checks active medicines against the patient’s conditions, drug interactions, and kidney function. This helps reveal potentially inappropriate treatment and dose-related risks.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Finding medicines to avoid, medicines needing caution or renal dose adjustment, drug-disease conflicts, and drug interactions, with evidence details and safer alternatives.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/langcare/langcare-mcp-fhir/beers-criteria
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 beers-criteria
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.

agentmods badge for langcare-beers-criteria

README.md
[![agentmods](https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/beers-criteria/github.svg)](https://agentmods.dev/skills/langcare/langcare-mcp-fhir/beers-criteria)
Your own site
<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/beers-criteria"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/beers-criteria/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.

agentmods 80×15 button for langcare-beers-criteria

Your own site · 80×15
<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/beers-criteria"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/beers-criteria.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 697 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00078 $0.00697
Opus 5 $0.00039 $0.00349
Sonnet 5 $0.00016 $0.00139
Haiku 4.5 $0.00008 $0.00070

Measured 12d ago against content hash 8c6a15813e49, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

langcare-beers-criteria 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 12d 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.

cma/skills/medication-management/beers-criteria/SKILL.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Beers Criteria Medication Review

When to Use This Skill

Use when reviewing medications for patients age 65 and older to identify potentially inappropriate prescriptions per AGS Beers Criteria 2023.

Clinical Workflow

  1. Use fhir_read to confirm patient age >= 65 from Patient.birthDate
  2. Use fhir_search to pull all active MedicationRequest resources
  3. Use fhir_search to pull active Condition resources for drug-disease interaction screening
  4. Use fhir_search to pull recent Observation resources (renal function for dose adjustments)
  5. Screen each medication against Beers Criteria categories: medications to avoid regardless of diagnosis, medications to avoid with specific conditions, medications to use with caution, drug-drug interactions to avoid, dose adjustments based on renal function
  6. Present findings with Beers category, quality of evidence, strength of recommendation, and safer alternatives

FHIR Resources

  • Patient -- Age verification (must be >= 65)
  • MedicationRequest -- Active medications to screen
  • Condition -- Active diagnoses for drug-disease interaction screening
  • Observation -- Renal function (eGFR/CrCl) for dose-based criteria

FHIR Query Examples

Pull Active Medications

fhir_search(resourceType="MedicationRequest", queryParams="patient=[patient-id]&status=active&_count=100")

Pull Active Conditions

fhir_search(resourceType="Condition", queryParams="patient=[patient-id]&clinical-status=active")

Pull Renal Function

fhir_search(resourceType="Observation", queryParams="patient=[patient-id]&code=33914-3&_sort=-date&_count=1")

Clinical Guidelines

  • AGS Beers Criteria 2023 (American Geriatrics Society)
  • STOPP/START Criteria v2 (Screening Tool of Older Persons' Prescriptions / Screening Tool to Alert to Right Treatment)
  • CMS Part D medication therapy management requirements

Interpretation Guide

  • Classify findings by Beers category: Table 2 (avoid regardless), Table 3 (avoid with specific conditions), Table 4 (use with caution), Table 5 (drug-drug interactions), Table 6 (dose adjustment for renal function)
  • Rate evidence quality: High, Moderate, Low, Very Low
  • Rate recommendation strength: Strong Avoid, Conditional Avoid, Use with Caution
  • For each flagged medication, provide: the Beers concern, the clinical rationale, safer alternative options, and whether discontinuation requires a taper

Read the full file on GitHub · 64 lines

Files

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.

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.

  1. 12d ago First seen · 64 lines · 78 tokens per session scan A 8c6a15813e49

Subscribe to this mod's changes

langcare-beers-criteria is a skill published in the GitHub repository langcare/langcare-mcp-fhir (55 stars, last pushed 5mo ago), licensed MIT. It adds 78 tokens to every session and 697 once invoked, about $0.0004 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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