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 LeonChaoX/qinyan-academic-skills --skill pubmed-databasegit clone --depth 1 https://github.com/LeonChaoX/qinyan-academic-skillsWrote 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/leonchaox/qinyan-academic-skills/pubmed-database)<a href="https://agentmods.dev/skills/leonchaox/qinyan-academic-skills/pubmed-database"><img src="https://agentmods.dev/badge/skills/leonchaox/qinyan-academic-skills/pubmed-database/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/leonchaox/qinyan-academic-skills/pubmed-database"><img src="https://agentmods.dev/badge/skills/leonchaox/qinyan-academic-skills/pubmed-database.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 | $0.00058 | $0.03621 |
| Opus 5 | $0.00029 | $0.01810 |
| Sonnet 5 | $0.00012 | $0.00724 |
| Haiku 4.5 | $0.00006 | $0.00362 |
Grade A, and why
pubmed-database scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get(search_url, params=params) This is a copy
100% identical to pubmed-database — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 459 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PubMed Database
Overview
PubMed is the U.S. National Library of Medicine's comprehensive database providing free access to MEDLINE and life sciences literature. Construct advanced queries with Boolean operators, MeSH terms, and field tags, access data programmatically via E-utilities API for systematic reviews and literature analysis.
When to Use This Skill
This skill should be used when:
- Searching for biomedical or life sciences research articles
- Constructing complex search queries with Boolean operators, field tags, or MeSH terms
- Conducting systematic literature reviews or meta-analyses
- Accessing PubMed data programmatically via the E-utilities API
- Finding articles by specific criteria (author, journal, publication date, article type)
- Retrieving citation information, abstracts, or full-text articles
- Working with PMIDs (PubMed IDs) or DOIs
- Creating automated workflows for literature monitoring or data extraction
Core Capabilities
1. Advanced Search Query Construction
Construct sophisticated PubMed queries using Boolean operators, field tags, and specialized syntax.
Basic Search Strategies:
- Combine concepts with Boolean operators (AND, OR, NOT)
- Use field tags to limit searches to specific record parts
- Employ phrase searching with double quotes for exact matches
- Apply wildcards for term variations
- Use proximity searching for terms within specified distances
Example Queries:
# Recent systematic reviews on diabetes treatment
diabetes mellitus[mh] AND treatment[tiab] AND systematic review[pt] AND 2023:2024[dp]
# Clinical trials comparing two drugs
(metformin[nm] OR insulin[nm]) AND diabetes mellitus, type 2[mh] AND randomized controlled trial[pt]
# Author-specific research
smith ja[au] AND cancer[tiab] AND 2023[dp] AND english[la]
When to consult search_syntax.md:
- Need comprehensive list of available field tags
- Require detailed explanation of search operators
- Constructing complex proximity searches
- Understanding automatic term mapping behavior
- Need specific syntax for date ranges, wildcards, or special characters
What ships with it
3 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.
- 11d ago First seen · 459 lines · 58 tokens per session scan A 1965718507ab
pubmed-database is a skill published in the GitHub repository LeonChaoX/qinyan-academic-skills (880 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 3,621 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to pubmed-database, differing in 3 lines, and is treated as a copy.
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