scholar-data

scholar-data is a Literature review & citations skill for AI agents, published by joshzyj in the open-scholar-skill repository on GitHub. Skillspace rates scholar-data D (56/100) and it passed the safety scan; the rating is based on static analysis only.

Comprehensive open data directory (100+ datasets across 14 categories) with auto-fetch capability, plus data collection instrument design, variable dictionaries, data management, IRB materials, and web/digital data collection for social science studies. Covers GSS, PSID, ACS, CPS, ESS, WVS, Afrobarometer, Eurobarometer, DHS, PISA, OECD, Eurostat, WHO, OpenAlex, Harvard Dataverse, ICPSR, Zenodo, OSF, and many more. Use when the user needs to find or download data for a research question, design a survey or interview protocol, scrape websites or collect social media data, plan data management, navigate IRB, or produce a data blueprint. Works best after /scholar-design and before /scholar-eda.

Grade
D
Quality
56 / 100
Safety
Passed
GitHub stars
102

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
74 / 100
Maturity
Structured: ships references or scripts
Security scan
Low-risk patterns
License
Not declared. Check the repository before reusing it.
Adoption
Adopted by 0 other repositories, in 0 collections

What the scanner flagged

  • mentions secrets in text

Not checked yet

  • Category is a classifier prediction; no model has read this skill 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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