Borrowing it
Nothing to install: this file belongs to u9401066/academic-figures-mcp. 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/u9401066/academic-figures-mcp/main/.claude/skills/pubmed-fulltext-access/SKILL.mdgit clone --depth 1 https://github.com/u9401066/academic-figures-mcpWrote 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/u9401066/academic-figures-mcp/pubmed-fulltext-access)<a href="https://agentmods.dev/skills/u9401066/academic-figures-mcp/pubmed-fulltext-access"><img src="https://agentmods.dev/badge/skills/u9401066/academic-figures-mcp/pubmed-fulltext-access/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/u9401066/academic-figures-mcp/pubmed-fulltext-access"><img src="https://agentmods.dev/badge/skills/u9401066/academic-figures-mcp/pubmed-fulltext-access.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 | $0.00045 | $0.01125 |
| Opus 5 | $0.00023 | $0.00562 |
| Sonnet 5 | $0.00009 | $0.00225 |
| Haiku 4.5 | $0.00005 | $0.00112 |
Grade A, and why
pubmed-fulltext-access 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 10d 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.
This is a copy
100% identical to pubmed-fulltext-access — 2 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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
全文取得指南
描述
目前的全文 workflow 以 get_fulltext 為核心。它會自動嘗試 Europe PMC、Unpaywall、CORE，必要時可擴展到更多來源。若需要圖表、文字探勘或機構訂閱連結，則搭配其他專用工具。
觸發條件
- 「我要看全文」
- 「有 PDF 嗎？」
- 「這篇有 open access 嗎？」
- 「幫我抓方法或結果段落」
- 提到 PMC、全文、PDF、開放取用
核心工具
1. get_fulltext
get_fulltext(identifier="PMC7096777")
get_fulltext(pmid="12345678")
get_fulltext(doi="10.1038/s41586-021-03819-2")
參數重點
identifier: 自動判斷 PMID、PMCID、DOIpmcid/pmid/doi: 也可分開傳sections: 只抓特定段落，例如"introduction,methods,results"include_pdf_links: 是否回傳 PDF 連結include_figures: 是否一起帶 figure metadataextended_sources: 是否擴展到更多來源
最常用範例
1. 直接抓 PMC 全文
get_fulltext(identifier="PMC7096777")
2. 只看方法與結果
get_fulltext(
pmid="12345678",
sections="methods,results"
)
3. 用 DOI 找 OA 版本
get_fulltext(
doi="10.1038/s41586-021-03819-2",
extended_sources=True
)
4. 全文連同 figures
get_fulltext(
pmcid="PMC7096777",
include_figures=True
)
圖表與視覺資料
取得文章圖表
get_article_figures(identifier="PMC12086443")
get_article_figures(pmid="40384072")
適合用在：
- 要單獨抽 figure caption 與 image URL
- 想快速找到流程圖、結果圖、顯微圖
- 需要比全文更結構化的圖像資料
文字探勘
取得 text-mined terms
get_text_mined_terms(pmcid="PMC7096777")
get_text_mined_terms(pmid="12345678", semantic_type="CHEMICAL")
常用 semantic_type:
GENE_PROTEINDISEASECHEMICALORGANISMGO_TERM
沒有 open access 時
機構訂閱工作流
list_resolver_presets()
configure_institutional_access(preset="exlibris_sfx", base_url="https://your-library...")
test_institutional_access()
get_institutional_link(pmid="12345678")
這一組工具適合：
- 已知機構有訂閱，但文章不是 OA
- 想把 PubMed/DOI 轉成圖書館 resolver 連結
建議工作流程
情境 1：從文章直接拿全文
fetch_article_details(pmids="12345678")
get_fulltext(pmid="12345678", sections="abstract,results")
情境 2：搜尋後挑代表性文章讀全文
unified_search(
query="remimazolam ICU sedation",
limit=10,
ranking="quality"
)
# 對選中的 PMID 再做全文抓取
get_fulltext(pmid="12345678", extended_sources=True)
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.
- 10d ago First seen · 187 lines · 45 tokens per session scan A d3724eec0353
pubmed-fulltext-access is a skill published in the GitHub repository u9401066/academic-figures-mcp (0 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,125 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to pubmed-fulltext-access, differing in 2 lines, and is treated as a copy.
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