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 YuanyuanMa03/academic-research-skills --skill pm-searchgit clone --depth 1 https://github.com/YuanyuanMa03/academic-research-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/yuanyuanma03/academic-research-skills/pm-search)<a href="https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/pm-search"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/pm-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/yuanyuanma03/academic-research-skills/pm-search"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/pm-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 | $0.00040 | $0.01271 |
| Opus 5.5 | $0.00016 | $0.00508 |
| Sonnet 5.5 | $0.00008 | $0.00254 |
| Haiku 4.5 | $0.00004 | $0.00127 |
Grade A, and why
pm-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 today.
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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PubMed Basic Search
Search PubMed for papers using keyword(s). Returns result count and structured result list via the NCBI E-utilities API — no login, no CAPTCHA, no DOM scraping.
Requirements
- Path 1 (default):
python3+ network access toeutils.ncbi.nlm.nih.gov. No browser needed. - Path 2 (fallback): a browser automation tool that can (a) navigate to a URL and (b) evaluate JavaScript in the page. Any such tool works (Chrome DevTools MCP, Playwright MCP, etc.) — do not assume a specific tool name.
Arguments
$ARGUMENTS contains the search keyword(s) in English or Chinese.
Steps
Path 1 — Standalone script (default)
Run from this skill's directory (single tool call):
python3 scripts/pubmed_api_search.py "YOUR_KEYWORDS" --limit 20
Useful flags: --page N, --sort date|relevance|pub_date|first_author|journal, --year-from 2022 --year-to 2026, --json (machine-readable), --mailto [email protected] (or env NCBI_MAILTO, joins NCBI's polite pool).
The script retries once on 429/5xx and reports failures to stderr with exit code 1. Exit code 0 with total: 0 means the query genuinely matched nothing.
Path 2 — Browser evaluate (only when no shell is available)
Use your browser tool to navigate to https://pubmed.ncbi.nlm.nih.gov/?term={URL_ENCODED_KEYWORDS}&size=20 (this shows the results page to the user), then evaluate the following script in the page. It calls the E-utilities API from page context — it never scrapes DOM.
Replace YOUR_KEYWORDS with the actual search terms:
async () => {
const query = "YOUR_KEYWORDS";
const page = 1, size = 20;
const retstart = (page - 1) * size;
// E-utilities esearch: get PMID list
const searchResp = await fetch(
`https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=${encodeURIComponent(query)}&retmax=${size}&retstart=${retstart}&retmode=json&sort=relevance`
);
const searchData = await searchResp.json();
const ids = searchData.esearchresult?.idlist || [];
const total = parseInt(searchData.esearchresult?.count || '0');
const queryTranslation = searchData.esearchresult?.querytranslation || '';
if (ids.length === 0) return { query, total: 0, results: [] };
// E-utilities esummary: batch get metadata
const sumResp = await fetch(
`https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=pubmed&id=${ids.join(',')}&retmode=json`
);
const sumData = await sumResp.json();
const results = ids.map((id, i) => {
const r = sumData.result?.[id] || {};
const doi = (r.articleids || []).find(a => a.idtype === 'doi')?.value || '';
return {
n: retstart + i + 1,
pmid: id,
title: r.title || '',
authors: (r.authors || []).map(a => a.name).join(', '),
journal: r.fulljournalname || '',
source: r.source || '',
pubdate: r.pubdate || '',
volume: r.volume || '',
issue: r.issue || '',
pages: r.pages || '',
doi,
pubtype: (r.pubtype || []).join(', ')
};
});
return { query, queryTranslation, total, page, size, results };
}
What ships with it
1 file 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.
- today First seen · 121 lines · 40 tokens per session scan A 42e6adce7a0e
pm-search is a skill published in the GitHub repository YuanyuanMa03/academic-research-skills (75 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 1,271 once invoked, about $0.0002 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 2026-10-29.
Other skills, from other repositories
paper2poster-poster
Use when the user wants to turn an academic paper into a conference poster, poster outline, poster copy deck, poster layout brief, poster.yaml style draft, or Paper2Poster-ready generation package. Trigger for paper-to-poster requests involving PDF papers, arXiv links, manuscripts, PPTX posters, conference…
manuscript-optimizer
Use when auditing, restructuring, or revising a research manuscript whose scientific question, claim hierarchy, evidence chain, section logic, figures, terminology, or prose may be unclear or out of sync. Apply before sentence-level polishing, especially for whole drafts, major revisions, resubmissions, overclaiming…
review-article-architecture
Use when writing, restructuring, or auditing a Review, survey, or Perspective rather than a research article, especially a commissioned one written across many sessions. Covers the governing plan document, drift detection, single-definition thesis and field judgements, section-owns-figure allocation, display-item…
write-scientific-manuscript
Diagnose and repair the clarity and logic of manuscript prose, journal-agnostic. Use when a passage is technically correct but hard to follow: buried topic sentences, missing logical bridges, ambiguous referents, abstract noun chains, overloaded sentences, incomplete comparisons with no stated dataset or metric or…
paper-reviewer
Referee-side skill for Nature Portfolio manuscripts: write a referee report, inventory every ask and sub-ask in received comments, grade drafted replies, and test reply readability. Check methodology, statistics, reporting, reproducibility and data/code availability. Preserve referee wording, numbering and order…
figure-planner
Use when designing, restructuring, or auditing manuscript figures and you need to define one main claim per figure, assign panel roles, align legends with the text, or decide what belongs in main figures versus supplement.