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 quality-measure-dashboardgit 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/quality-measure-dashboard)<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/quality-measure-dashboard"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/quality-measure-dashboard/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/quality-measure-dashboard"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/quality-measure-dashboard.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 | $0.00123 | $0.03559 |
| Opus 5.5 | $0.00049 | $0.01424 |
| Sonnet 5.5 | $0.00025 | $0.00712 |
| Haiku 4.5 | $0.00012 | $0.00356 |
Grade A, and why
quality-measure-dashboard 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 — 295 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quality Measure Dashboard
Overview
Calculate formal HEDIS and CMS quality measures using FHIR R4 data. Apply numerator/denominator/exclusion logic per measure specification. Report measure rates, compare against benchmarks, identify patients falling out of compliance, and track trends. Supports measures for diabetes care (A1c, eye exam, nephropathy), hypertension control, breast cancer screening, colorectal cancer screening, depression screening, statin therapy, and tobacco cessation. See references/hedis-measure-definitions.md for full specifications.
FHIR Resources Used
| Resource | Purpose | Key Fields |
|---|---|---|
| Condition | Denominator identification (diagnosis) | code, clinicalStatus, onsetDateTime, subject |
| Patient | Demographics for age/sex stratification | birthDate, gender |
| Observation | Lab results, vitals, screening scores | code, valueQuantity, effectiveDateTime, status |
| Procedure | Screening procedures, surgeries (exclusions) | code, performedDateTime, status |
| Encounter | Visit-based measure eligibility | class, period, type, status |
| MedicationRequest | Medication-based measures (statin therapy) | medicationCodeableConcept, status, authoredOn |
| DiagnosticReport | Screening results (mammogram, colonoscopy) | code, effectiveDateTime, status, conclusion |
| Immunization | Immunization-related measures | vaccineCode, occurrenceDateTime, status |
Instructions
Step 1: Select Measures to Calculate
Determine which measures the user wants. If unspecified, calculate the core set:
- HBD - Hemoglobin A1c Control for Patients with Diabetes (A1c < 8%)
- CBP - Controlling High Blood Pressure (BP < 140/90)
- BCS - Breast Cancer Screening (mammogram in 27 months)
- COL - Colorectal Cancer Screening (per USPSTF intervals)
- DSF - Depression Screening and Follow-Up
- SPD - Statin Therapy for Patients with Diabetes
- TCC - Tobacco Cessation Counseling
Step 2: Build Denominator Population
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.
- 2mo ago First seen · 295 lines · 123 tokens per session scan A c48d55cd45b3
quality-measure-dashboard is a skill published in the GitHub repository langcare/langcare-mcp-fhir (71 stars, last pushed 6mo ago), licensed MIT. It adds 123 tokens to every session and 3,559 once invoked, about $0.0005 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.
quality-measure-dashboard compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| quality-measure-dashboardlangcare/langcare-mcp-fhir | Skill | 71 | 6mo ago | MIT | A | 123 | 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 |