Borrowing it
Nothing to install: this file belongs to monarch-initiative/dismech. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/monarch-initiative/dismech/main/.claude/skills/collect-care-guidelines/SKILL.mdgit clone --depth 1 https://github.com/monarch-initiative/dismechWrote 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/monarch-initiative/dismech/collect-care-guidelines)<a href="https://agentmods.dev/skills/monarch-initiative/dismech/collect-care-guidelines"><img src="https://agentmods.dev/badge/skills/monarch-initiative/dismech/collect-care-guidelines/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/monarch-initiative/dismech/collect-care-guidelines"><img src="https://agentmods.dev/badge/skills/monarch-initiative/dismech/collect-care-guidelines.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00087 | $0.01652 |
| Opus 5 | $0.00044 | $0.00826 |
| Sonnet 5 | $0.00017 | $0.00330 |
| Haiku 4.5 | $0.00009 | $0.00165 |
Grade A, and why
collect-care-guidelines 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 8d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Collect Clinical Care Guidelines Skill
Overview
This skill finds the clinical care guidelines that describe the management of a dismech disorder, so their phenotype and treatment content can be mined against the existing knowledge-base entry (the workflow first used for the Fanconi anemia gap analysis, issue #4878).
A "clinical care description" here is operationalized as a PubMed citation whose
Publication Type is Practice Guideline, published within the last 10
years (configurable). PubMed's Practice Guideline publication type is a
curated NLM tag applied to society/consensus management guidelines, which makes
it a high-precision filter for care descriptions — far better than free-text
searching for the word "guideline".
The output is a tab-delimited citation table (one row per disorder × PMID) plus a JSONL discovery record that doubles as a prioritization ranking.
When to use
- Building an initial care-guideline citation set for a batch of disorders.
- Refreshing an existing set with newly published guidelines.
- Prioritizing which disorders have the richest recent guideline evidence to mine for phenotype/treatment gaps.
The workflow (two steps)
The helper script scripts/collect_guidelines.py uses NCBI E-utilities
(esearch + esummary) with only the standard library plus PyYAML. Run it from
the repo root.
Step 1 — search
For each disorder, it builds a clean search term (the top-level MONDO mapping
label when present, else the name field with underscores as spaces) and runs:
esearch db=pubmed
term=("<disease name>"[MeSH Terms] OR "<disease name>"[Title/Abstract])
AND "Practice Guideline"[Publication Type]
datetype=pdat reldate=3650 # last 10 years
The disease phrase must be field-tagged ([MeSH Terms] / [Title/Abstract]).
A bare quoted phrase lets PubMed's Automatic Term Mapping shatter an unmatched
name into individual all-fields words — e.g. "Alsahan-Harris syndrome" collapses
to Harris + syndrome and falsely returns dozens of unrelated guidelines.
Field-tagging makes an unmatched disorder correctly return zero.
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.
- 8d ago Changed 40b608b03c52
- 12d ago First seen · 145 lines · 87 tokens per session scan A e53fa72753a1
collect-care-guidelines is a skill published in the GitHub repository monarch-initiative/dismech (61 stars, last pushed today), licensed BSD-3-Clause. It adds 87 tokens to every session and 1,652 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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