scholar-megasearch

scholar-megasearch is a Literature review & citations skill for AI agents, published by TaewoooPark in the scholar-megasearch repository on GitHub. Skillspace rates scholar-megasearch D (68/100) and it passed the safety scan; the rating is based on static analysis only.

Massive multi-source academic literature search via subagent orchestration. Fans out parallel searchers across every available scholarly source — arXiv, Semantic Scholar, Crossref, OpenAlex, PubMed/PMC, bioRxiv/medRxiv, DOAJ, CORE, BASE, DBLP, IACR, SSRN, Zenodo, Unpaywall, plus web/GitHub — then deduplicates by DOI/arXiv-id/title into one ranked corpus and synthesizes it. Use when the user wants a broad/exhaustive literature sweep, a large-scale paper search, a systematic review corpus, citation snowballing, or to find as many papers as possible on a topic across many databases at once. Triggers: "massive literature search", "literature review", "search across every database", "systematic search", "mega search", "search every source", "exhaustive search". Localized trigger phrases in other languages map to the same intent.

Grade
D
Quality
68 / 100
Safety
Passed
GitHub stars
21

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

Our review

Architecture
84 / 100
Maturity
Structured: ships references or scripts
Security scan
Low-risk patterns
License
MIT
Adoption
Adopted by 0 other repositories, in 0 collections

What the scanner flagged

  • mentions secrets in text

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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