Borrowing it
Nothing to install: this file belongs to u9401066/med-paper-assistant. 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/med-paper-assistant/master/.claude/skills/pubmed-systematic-search/SKILL.mdgit clone --depth 1 https://github.com/u9401066/med-paper-assistantWrote 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/med-paper-assistant/pubmed-systematic-search)<a href="https://agentmods.dev/skills/u9401066/med-paper-assistant/pubmed-systematic-search"><img src="https://agentmods.dev/badge/skills/u9401066/med-paper-assistant/pubmed-systematic-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/med-paper-assistant/pubmed-systematic-search"><img src="https://agentmods.dev/badge/skills/u9401066/med-paper-assistant/pubmed-systematic-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00048 | $0.01297 |
| Opus 5.5 | $0.00019 | $0.00519 |
| Sonnet 5.5 | $0.00010 | $0.00259 |
| Haiku 4.5 | $0.00005 | $0.00130 |
Grade A, and why
pubmed-systematic-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 1mo 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- pubmed-systematic-search — 100% identical, 2 lines differ
- pubmed-systematic-search — 100% identical, 2 lines differ
- pubmed-systematic-search — 100% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
系統性文獻搜尋
描述
這個 workflow 用在「要找得完整」而不是「先快速看一下」的情境。核心做法是先用 generate_search_queries 取得 MeSH、同義詞與建議查詢,再由 Agent 或使用者組裝成明確的 Boolean 查詢,最後用 unified_search 執行。
觸發條件
- 「系統性搜尋」
- 「完整搜尋」
- 「文獻回顧」
- 「comprehensive search」
- 「systematic review」
- 提到 MeSH、同義詞擴展、搜尋策略
正確工作流程
generate_search_queries
→ 整理 MeSH / 同義詞 / suggested_queries
→ 手動或由 Agent 組 Boolean 查詢
→ analyze_search_query
→ unified_search
→ fetch_article_details / prepare_export / save_pipeline
目前沒有公開的獨立合併工具工作流。每一次
unified_search本身就會做多來源整合與去重;如果你跑多輪策略,做法應該是比較各輪結果、調整查詢,或把流程保存成 pipeline,而不是依賴舊版 merge 思路。
Step 1: 取得搜尋素材
generate_search_queries(
topic="remimazolam ICU sedation",
strategy="comprehensive"
)
strategy 選項
comprehensive: 預設,適合完整搜尋focused: 收斂到較高證據等級exploratory: 放寬,找更多變體與同義詞
你真正要用的欄位
mesh_terms: 標準詞彙與對應同義詞all_synonyms: 可直接組 OR 群組suggested_queries: 當作參考,不是最後答案pubmed_translation: 檢查 PubMed 實際如何理解查詢
Step 2: 組裝 Boolean 查詢
範例:從素材組出可執行查詢
query = '''
("Intensive Care Units"[Title/Abstract] OR ICU[Title/Abstract] OR "critical care"[Title/Abstract])
AND
(remimazolam[Title/Abstract] OR "CNS 7056"[Title/Abstract] OR "ONO 2745"[Title/Abstract])
AND
(sedation[Title/Abstract] OR "procedural sedation"[Title/Abstract])
'''
兩個原則
- 主概念之間通常用
AND - 同義詞與別名通常用
OR
Step 3: 執行前先分析
analyze_search_query(query=query)
這一步用來確認:
- 查詢是否太寬或太窄
- PubMed translation 是否符合預期
- 有沒有拼字或概念錯置
Step 4: 執行搜尋
unified_search(
query=query,
sources="pubmed,europe_pmc,openalex",
limit=50,
ranking="quality",
filters="year:2020-2025, species:humans, clinical:therapy",
output_format="json"
)
常用調整方式
- 想更完整:加入
options="preprints" - 想更快:加入
options="shallow" - 不要自動放寬:加入
options="no_relax" - 重視新近性:
ranking="recency" - 重視證據品質:
ranking="quality"
完整範例
情境:完整搜尋 remimazolam ICU sedation
# Step 1: 取得 MeSH 與同義詞素材
materials = generate_search_queries(
topic="remimazolam ICU sedation",
strategy="comprehensive"
)
# Step 2: 組裝查詢
query = '''
("intensive care"[Title/Abstract] OR ICU[Title/Abstract] OR "critical care"[Title/Abstract])
AND
(remimazolam[Title/Abstract] OR "CNS 7056"[Title/Abstract] OR "ONO 2745"[Title/Abstract])
AND
(sedation[Title/Abstract] OR "procedural sedation"[Title/Abstract])
'''
# Step 3: 先分析
analyze_search_query(query=query)
# Step 4: 再執行
unified_search(
query=query,
limit=50,
ranking="quality",
filters="year:2020-2025, 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.
- 1mo ago First seen · 186 lines · 48 tokens per session scan A 3e3fd8c549e6
pubmed-systematic-search is a skill published in the GitHub repository u9401066/med-paper-assistant (12 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 48 tokens to every session and 1,297 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 2026-08-30.
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