radiology-citation
radiology-citation is a Literature review & citations skill for AI agents, published by huang-sir1 in the radiology-skills repository on GitHub. Skillspace rates radiology-citation C (72/100) and it passed the safety scan; the rating is based on static analysis only.
Turn manuscript text, claims, figure/table statements, abstracts, slides, or novelty/comparison assertions into verified, imaging-journal-scoped citation candidates and export one reference-manager-ready file (RIS, EndNote ENW, or BibTeX). Use when the user needs references for an imaging paper, wants supporting citations, wants a two-pass claim/citation/numerical verification gate, needs to check whether a cited source actually says the claimed thing, scope citations to radiology/imaging journals (Radiology, Radiology: AI, RadioGraphics, AJR, European Radiology, JACR, etc.), verify a DOI/PMID, or export a bibliography. Verifies identifiers before formatting and never fabricates DOIs, pages, volumes, journal metadata, or source support.
- Grade
- C
- Quality
- 72 / 100
- Safety
- Passed
- GitHub stars
- 819
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
- 96 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
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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