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-pico-search/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-pico-search)<a href="https://agentmods.dev/skills/u9401066/academic-figures-mcp/pubmed-pico-search"><img src="https://agentmods.dev/badge/skills/u9401066/academic-figures-mcp/pubmed-pico-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/u9401066/academic-figures-mcp/pubmed-pico-search"><img src="https://agentmods.dev/badge/skills/u9401066/academic-figures-mcp/pubmed-pico-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 | $0.00047 | $0.01396 |
| Opus 5 | $0.00023 | $0.00698 |
| Sonnet 5 | $0.00009 | $0.00279 |
| Haiku 4.5 | $0.00005 | $0.00140 |
Grade A, and why
pubmed-pico-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 12d 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 — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PICO 臨床問題搜尋
描述
這個 workflow 用在臨床比較問題。先把自然語言拆成 PICO,再對各元素做術語擴展,最後組成一個可以執行的臨床查詢並用 unified_search 搜尋。
觸發條件
- 「A 比 B 好嗎?」
- 「哪個治療效果更好?」
- 「在某類病人中,某藥是否改善某結果?」
- 提到 PICO、臨床問題、療效比較
PICO 元素
| 元素 | 說明 | 例子 |
|---|---|---|
P |
Population | ICU patients |
I |
Intervention | remimazolam |
C |
Comparison | propofol |
O |
Outcome | delirium |
正確工作流程
parse_pico
→ generate_search_queries × 每個 PICO 元素
→ 組合 Boolean 查詢
→ analyze_search_query
→ unified_search
這個流程不再依賴舊的逐步搜尋與合併流程。臨床問題的重點是把 PICO 結構轉成一個清楚的臨床查詢,再用 unified_search 執行。
Step 1: 解析 PICO
自然語言輸入
parse_pico(
description="remimazolam 在 ICU 鎮靜比 propofol 好嗎?會減少 delirium 嗎?"
)
或直接提供結構化欄位
parse_pico(
description="",
p="ICU patients",
i="remimazolam",
c="propofol",
o="delirium"
)
你要關注的輸出是:
pico: 解析出的 P/I/C/Oquestion_type: 例如therapy,diagnosis,prognosis,etiologysuggested_filter: 後續可轉進filters="clinical:..."
Step 2: 擴展各元素術語
generate_search_queries(topic="ICU patients")
generate_search_queries(topic="remimazolam")
generate_search_queries(topic="propofol")
generate_search_queries(topic="delirium")
實務上,只對有值的元素呼叫即可。如果 C 不明確,就不要硬塞進查詢。
Step 3: 組 Boolean 查詢
高精確度版本
query = '''
("intensive care"[Title/Abstract] OR ICU[Title/Abstract])
AND
(remimazolam[Title/Abstract] OR "CNS 7056"[Title/Abstract])
AND
(propofol[Title/Abstract] OR Diprivan[Title/Abstract])
AND
(delirium[Title/Abstract] OR "Delirium"[MeSH Terms])
'''
高召回版本
query = '''
("intensive care"[Title/Abstract] OR ICU[Title/Abstract])
AND
((remimazolam[Title/Abstract] OR "CNS 7056"[Title/Abstract])
OR
(propofol[Title/Abstract] OR Diprivan[Title/Abstract]))
AND
(delirium[Title/Abstract] OR sedation[Title/Abstract])
'''
Step 4: 執行前分析
analyze_search_query(query=query)
這一步可以先檢查查詢是否合理,再決定要不要執行。
Step 5: 執行搜尋
unified_search(
query=query,
limit=50,
ranking="quality",
filters="year:2018-2025, species:humans, clinical:therapy",
output_format="json"
)
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.
- 12d ago First seen · 210 lines · 47 tokens per session scan A ede15df3a8f8
pubmed-pico-search is a skill published in the GitHub repository u9401066/academic-figures-mcp (0 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 47 tokens to every session and 1,396 once invoked, about $0.0002 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.
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