Borrowing it
Nothing to install: this file belongs to Dariolex/pubmed-search-agent. 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/Dariolex/pubmed-search-agent/master/.claude/skills/pubmed-search/SKILL.mdgit clone --depth 1 https://github.com/Dariolex/pubmed-search-agentWrote 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/dariolex/pubmed-search-agent/pubmed-search)<a href="https://agentmods.dev/skills/dariolex/pubmed-search-agent/pubmed-search"><img src="https://agentmods.dev/badge/skills/dariolex/pubmed-search-agent/pubmed-search/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/dariolex/pubmed-search-agent/pubmed-search"><img src="https://agentmods.dev/badge/skills/dariolex/pubmed-search-agent/pubmed-search.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 | $0.00092 | $0.02538 |
| Opus 5 | $0.00046 | $0.01269 |
| Sonnet 5 | $0.00018 | $0.00508 |
| Haiku 4.5 | $0.00009 | $0.00254 |
Grade A, and why
pubmed-search 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 11d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PubMed NL Search
Trasforma una richiesta in linguaggio naturale in una ricerca PubMed reale, poi filtra i risultati per pertinenza rispetto all'intento dell'utente.
Eseguire i comandi Python dalla radice del progetto (dove c'è pytest.ini), con
src sul PYTHONPATH — es. PYTHONPATH=src python -m nl_query_translator ....
Serve un file .env valido con NCBI_API_KEY, NCBI_TOOL_NAME, NCBI_EMAIL.
Flusso
1. Estrai il JSON intermedio dalla richiesta
Analizza la richiesta NL e costruisci questo JSON (schema esteso con provenienza):
{
"intento_originale": "<la richiesta dell'utente, verbatim>",
"concetti": [
{"termine": "<concetto>", "sinonimi": ["<variante>"], "mesh": "<termine MeSH o null>", "provenienza": "<perché estratto>"}
],
"operatore_tra_concetti": "AND",
"esclusioni": [{"termine": "<da escludere>", "campo": "pt", "provenienza": "<perché>"}],
"filtri": {
"date": {"da": "<anno>", "a": "<anno>", "tipo": "dp"},
"tipi_studio": ["<publication type>"],
"lingua": "<lingua o null>",
"brevetto": true
}
}
Linee guida per l'estrazione:
- Concetti: i nuclei clinici/scientifici della richiesta. Aggiungi
sinonimiutili (varianti terminologiche, non traduzioni). Per il campomesh, se hai un candidato plausibile (es.melanoma), non limitarti al tuo giudizio: verificalo con il resolver (vedi sotto) prima di popolarlo nel JSON finale. - operatore_tra_concetti:
ANDdi norma (l'utente vuole tutti i concetti insieme). UsaORsolo se la richiesta è esplicitamente alternativa ("melanoma o carcinoma"). - Esclusioni: frasi come "escludendo X", "senza X", "non case report" →
NOT. Per i tipi di pubblicazione usacampo: "pt"; per termini liberi ometticampo. - Filtri date: "ultimi 3 anni" → calcola dalla data odierna (
da= anno corrente − 3,a= anno corrente).tipo:dp(data di pubblicazione) di default. - Tipi di studio: "trial randomizzati" →
randomized controlled trial; "meta-analisi" →meta-analysis; "review" →review. Più tipi vengono uniti in OR automaticamente. - Lingua: solo se la richiesta la specifica ("in inglese" →
english). - Brevetto: imposta
brevetto: truequando la richiesta chiede articoli i cui autori dichiarano un brevetto ("che dichiarano un brevetto", "con brevetto registrato", "autori con brevetti"); ometti il campo (non impostarlo afalse) quando non richiesto. AggiungeAND "patent*"[cois]alla query. Attenzione: PubMed non indicizza i brevetti — il filtro cerca nel Conflict of Interest Statement, che è testo libero. Cattura quindi anche le dichiarazioni negative ("gli autori non detengono brevetti"): vanno scartate leggendocoi_statementnella fase 5.
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.
- 11d ago First seen · 180 lines · 92 tokens per session scan A c061246b48bc
pubmed-search is a skill published in the GitHub repository Dariolex/pubmed-search-agent (2 stars, last pushed 1mo ago), licensed MIT. It adds 92 tokens to every session and 2,538 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
noodle-biomedical-literature-discovery
Find, inspect, compare, and traverse public biomedical research literature. Use for PubMed or scholarly paper search, publication details, PMID/DOI/PMCID lookup, related papers, citation paths, semantic literature neighborhoods, corpus coverage, or questions asking what research exists about a gene, variant…
noodle-biomedical-literature-discovery-mcp
Select Noodle Biomedical Literature Discovery MCP from Biorouter for public biomedical paper search, PMID DOI or PMCID lookup, publication inspection, related papers, citation or semantic graph traversal, and corpus metadata even when the user does not know the Noodle name.
deep-research
Use when the user explicitly needs a rigorous, cited, formal research report on a complex scientific, technical, policy, or market topic.
drug-discovery
Drug discovery: ChEMBL search, drug-likeness, interactions.
detecting-pv-signals
Computes disproportionality signals — PRR, ROR, EBGM, and IC (BCPNN) — over FAERS / OpenFDA drug-event data to flag potential safety signals. Use when the user wants to mine spontaneous-report data for drug-reaction associations, build a 2x2 contingency table, compute a Proportional Reporting Ratio or Reporting Odds…
coding-icd10
Suggests candidate ICD-10-CM diagnosis codes (and ICD-10-PCS procedure codes) for diagnoses and procedures extracted by OpenMed, with rationale and a human-coder caveat. Use when the user wants to code a problem list, map a diagnosis span to a billable ICD-10-CM code, route a finding to the right chapter, cross-walk…