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 allergy-adverse-reaction-summarygit 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/allergy-adverse-reaction-summary)<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/allergy-adverse-reaction-summary"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/allergy-adverse-reaction-summary/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/allergy-adverse-reaction-summary"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/allergy-adverse-reaction-summary.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 | $0.00093 | $0.03231 |
| Opus 5.5 | $0.00037 | $0.01292 |
| Sonnet 5.5 | $0.00019 | $0.00646 |
| Haiku 4.5 | $0.00009 | $0.00323 |
Grade A, and why
allergy-adverse-reaction-summary 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 — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Allergy & Adverse Reaction Summary
Overview
Pull all AllergyIntolerance resources for a patient. Categorize by type (drug, food, environmental). Grade severity and criticality. Flag high-risk allergies that require special clinical attention (anaphylaxis history, contrast dye, latex, NSAID sensitivity). Cross-reference against current medications to detect active conflicts. Output a structured summary with actionable safety flags.
FHIR Resources Used
| Resource | Purpose | Search Parameters |
|---|---|---|
| AllergyIntolerance | Allergy and intolerance records | patient, clinical-status |
| MedicationRequest | Current medications for conflict detection | patient, status=active |
| Observation | IgE levels if available | patient, code (LOINC) |
Instructions
Step 1: Pull All AllergyIntolerance Resources
Tool: fhir_search
resourceType: "AllergyIntolerance"
queryParams: "patient=[patient-id]"
Retrieve all records regardless of clinical status to capture full history. For each entry extract:
code.coding: Substance (RxNorm for drugs, SNOMED CT for non-drugs)clinicalStatus: active, inactive, resolvedverificationStatus: confirmed, unconfirmed, refuted, entered-in-errortype: allergy vs intolerancecategory: food, medication, environment, biologiccriticality: low, high, unable-to-assessreaction[]: Each reaction eventmanifestation[].coding[].display: What happened (hives, anaphylaxis, rash, etc.)severity: mild, moderate, severeonset: When the reaction occurredsubstance: Specific substance if different from the top-level code
onsetDateTime: When allergy was first identifiedrecorder: Who documented itnote: Free-text notes
Step 2: Categorize Allergies
Group into four categories:
Drug Allergies (category = "medication"):
- Identify drug class from the substance code or name
- Check for class-level allergies vs specific drug allergies
- Note if the allergy is to a drug class (e.g., "penicillins") vs specific drug (e.g., "amoxicillin")
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 · 338 lines · 93 tokens per session scan A a456f549217c
allergy-adverse-reaction-summary is a skill published in the GitHub repository langcare/langcare-mcp-fhir (71 stars, last pushed 6mo ago), licensed MIT. It adds 93 tokens to every session and 3,231 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.
allergy-adverse-reaction-summary compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| allergy-adverse-reaction-summarylangcare/langcare-mcp-fhir | Skill | 71 | 6mo ago | MIT | A | 93 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| 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 |