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-paper-exploration/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-paper-exploration)<a href="https://agentmods.dev/skills/u9401066/academic-figures-mcp/pubmed-paper-exploration"><img src="https://agentmods.dev/badge/skills/u9401066/academic-figures-mcp/pubmed-paper-exploration/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-paper-exploration"><img src="https://agentmods.dev/badge/skills/u9401066/academic-figures-mcp/pubmed-paper-exploration.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 | $0.00056 | $0.01241 |
| Opus 5 | $0.00028 | $0.00620 |
| Sonnet 5 | $0.00011 | $0.00248 |
| Haiku 4.5 | $0.00006 | $0.00124 |
Grade A, and why
pubmed-paper-exploration 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.
This is a copy
100% identical to pubmed-paper-exploration — 20 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
論文深度探索
描述
這個 workflow 用在「已經有一篇關鍵論文」之後的深挖。你可以沿三個方向展開:相似文獻、這篇引用了誰、誰又引用了它,再進一步建立 citation tree 或研究時間軸。
觸發條件
- 「這篇論文的相關研究」
- 「誰引用這篇?」
- 「這篇建立在誰的研究上?」
- 「幫我畫這篇論文的 citation tree」
- 已提供 PMID 或明確的種子論文標題
如果還沒有 PMID
先用 unified_search 找到種子論文:
unified_search(
query="remimazolam randomized controlled trial",
limit=5,
ranking="quality"
)
拿到 PMID 後,再進入下面 workflow。
核心探索方向
| 工具 | 作用 | 方向 |
|---|---|---|
fetch_article_details |
取得文章完整資訊 | 當前論文 |
find_related_articles |
找主題相近文章 | 橫向 |
get_article_references |
找這篇引用了誰 | 往過去 |
find_citing_articles |
找誰引用這篇 | 往未來 |
get_citation_metrics |
看引用影響力 | 評估重要性 |
build_citation_tree |
建立引用網路 | 視覺化 |
build_research_timeline |
建立時間軸 | 演化脈絡 |
最常用範例
1. 先拿文章細節
fetch_article_details(pmids="30217674")
2. 找相似文章
find_related_articles(pmid="30217674", limit=10)
3. 找這篇引用了誰
get_article_references(pmid="30217674", limit=30)
4. 找誰引用了這篇
find_citing_articles(pmid="30217674", limit=20)
5. 看哪幾篇最有影響力
get_citation_metrics(
pmids="30217674,35678901,34567890",
sort_by="relative_citation_ratio"
)
6. 直接建 citation tree
build_citation_tree(
pmid="30217674",
depth=2,
direction="both",
output_format="mermaid"
)
建議工作流程
情境:從一篇關鍵 RCT 往外展開
# Step 1: 當前論文
fetch_article_details(pmids="30217674")
# Step 2: 三個方向同時展開
find_related_articles(pmid="30217674", limit=10)
get_article_references(pmid="30217674", limit=20)
find_citing_articles(pmid="30217674", limit=20)
# Step 3: 對重要 PMIDs 做引用影響力排序
get_citation_metrics(
pmids="35678901,34567890,33456789",
sort_by="citation_count"
)
# Step 4: 視覺化引用網路
build_citation_tree(
pmid="30217674",
depth=2,
direction="both",
output_format="cytoscape"
)
如果想看時間演化
以單篇或一組 PMID 建時間軸
build_research_timeline(
pmids="30217674,35678901,34567890",
topic="Remimazolam Clinical Development",
output_format="mermaid"
)
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 · 198 lines · 56 tokens per session scan A cac9d98bf623
pubmed-paper-exploration is a skill published in the GitHub repository u9401066/academic-figures-mcp (0 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 56 tokens to every session and 1,241 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to pubmed-paper-exploration, differing in 20 lines, and is treated as a copy.
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