Borrowing it
Nothing to install: this file belongs to u9401066/rootcause-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/rootcause-mcp/master/.claude/skills/pubmed-multi-source-search/SKILL.mdgit clone --depth 1 https://github.com/u9401066/rootcause-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/rootcause-mcp/pubmed-multi-source-search)<a href="https://agentmods.dev/skills/u9401066/rootcause-mcp/pubmed-multi-source-search"><img src="https://agentmods.dev/badge/skills/u9401066/rootcause-mcp/pubmed-multi-source-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/rootcause-mcp/pubmed-multi-source-search"><img src="https://agentmods.dev/badge/skills/u9401066/rootcause-mcp/pubmed-multi-source-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 | $0.00044 | $0.01088 |
| Opus 5 | $0.00022 | $0.00544 |
| Sonnet 5 | $0.00009 | $0.00218 |
| Haiku 4.5 | $0.00004 | $0.00109 |
Grade A, and why
pubmed-multi-source-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 8d 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-multi-source-search — 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.
多來源綜合搜尋
描述
目前公開的多來源搜尋入口是 unified_search。它會自動在 PubMed、OpenAlex、Semantic Scholar、Europe PMC、CrossRef 之間分流,並在單次搜尋內做整合與去重。
觸發條件
- 「跨資料庫搜尋」
- 「綜合搜尋」
- 「不要只看 PubMed」
- 提到 OpenAlex、Semantic Scholar、Europe PMC、preprint
- 需要跨來源補足 coverage
核心原則
新 workflow 不再直接依賴多個來源別 MCP 工具。對大多數文獻搜尋情境,應優先使用
unified_search,而不是舊的來源別工具名稱。
核心工具
unified_search(
query="machine learning drug discovery",
sources="pubmed,openalex,semantic_scholar,europe_pmc",
limit=25,
ranking="balanced",
output_format="json"
)
sources 可選值
pubmedopenalexsemantic_scholareurope_pmccrossref
如果不指定,系統會自動選來源。
常見用法
1. 廣泛覆蓋
unified_search(
query="machine learning drug discovery",
limit=30,
ranking="balanced"
)
2. 只看生醫核心來源
unified_search(
query="sepsis biomarkers",
sources="pubmed,europe_pmc",
limit=25,
ranking="quality"
)
3. 納入預印本
unified_search(
query="COVID-19 vaccine efficacy",
sources="pubmed,europe_pmc,openalex",
options="preprints",
limit=30,
ranking="recency"
)
4. 看高影響力跨領域文獻
unified_search(
query="foundation models pathology",
sources="pubmed,openalex,semantic_scholar",
limit=30,
ranking="impact"
)
5. 程式化後處理
unified_search(
query="CRISPR gene therapy",
sources="pubmed,openalex,semantic_scholar,europe_pmc",
limit=20,
output_format="json"
)
建議工作流程
情境 1:跨來源找完整 coverage
unified_search(
query="remimazolam sedation",
sources="pubmed,europe_pmc,openalex,semantic_scholar",
limit=30,
ranking="balanced"
)
情境 2:先找文獻,再補全文
unified_search(
query="machine learning radiology",
limit=20,
output_format="json"
)
# 對選中的 PMID / DOI 進一步抓全文
get_fulltext(pmid="12345678", extended_sources=True)
情境 3:跨來源搜尋後做探索
unified_search(
query="CAR-T lymphoma",
limit=15,
ranking="impact"
)
find_related_articles(pmid="12345678")
find_citing_articles(pmid="12345678")
get_citation_metrics(pmids="12345678,23456789")
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.
- 8d ago First seen · 187 lines · 44 tokens per session scan A 8d47f294fb42
pubmed-multi-source-search is a skill published in the GitHub repository u9401066/rootcause-mcp (0 stars, last pushed 5d ago), licensed Apache-2.0. It adds 44 tokens to every session and 1,088 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-multi-source-search, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
assembling-fhir-bundles
Package multiple FHIR R4 resources produced from OpenMed output into a single valid transaction Bundle ready to POST to an EHR, using OpenMed's verified bundle assembler openmed.clinical.exporters.fhir.tobundle. Covers deterministic urn:uuid fullUrls, automatic in-Bundle reference rewriting, request blocks…
auditing-part11-trails
Generates and verifies 21 CFR Part 11-style audit trails — who/what/when, electronic signatures, and tamper-evidence — for OpenMed pipelines in GxP and clinical-trial (GCP) settings. Use when the user runs OpenMed in a regulated/validated environment and needs an attributable, time-stamped, tamper-evident record of…
batch-processing-clinical-text
Run large-scale batch NER, PII extraction, or de-identification over many clinical notes on-device with OpenMed, with sharding, checkpointing, resumability, and append-only JSONL output. Use when the user needs to process a corpus or folder of notes, de-identify a dataset, run NER over thousands of documents, build a…
coding-hcc-risk-adjustment
Maps chronic conditions extracted by OpenMed to CMS-HCC V28 risk-adjustment categories and estimates a RAF (Risk Adjustment Factor) score as decision support. Use when the user wants to surface risk-adjustable diagnoses from notes, map ICD-10-CM codes to HCC categories, estimate or reconcile a patient/panel RAF, find…
detecting-pv-signals
Computes disproportionality signals — PRR, ROR, EBGM, and IC (BCPNN) — over FAERS / OpenFDA drug-event data to flag potential safety signals. Use when the user wants to mine spontaneous-report data for drug-reaction associations, build a 2x2 contingency table, compute a Proportional Reporting Ratio or Reporting Odds…
exporting-to-fhir
Convert OpenMed NER output (entities from openmed.analyzetext) into FHIR R4 resources — Condition, MedicationStatement, Observation — using OpenMed's built-in FHIR R4 export helpers in openmed.clinical.exporters. Covers the verified CodeableConcept builder (coding, codeableconcept, systemuri), deterministic fullUrl…