skill-find-papers
skill-find-papers is a Literature review & citations skill for AI agents, published by zifangchen in the skill-find-papers repository on GitHub. Skillspace rates skill-find-papers C (77/100) and it passed the safety scan; the rating is based on static analysis only.
Find, rank, summarize, and track high-quality research papers with Scholar MCP, accept user-submitted PDFs, DOIs, or links through a persistent local inbox as special-interest signals, then create evidence-rich bilingual Feishu deep-read documents with detailed abstracts, contributions, methods, figures, and verified links using lark-cli. Use for recurring paper recommendations, weekly research digests, receiving papers directly from the user, processing paper feedback, changing research interests, or creating detailed paper notes in Feishu.
- Grade
- C
- Quality
- 77 / 100
- Safety
- Passed
- GitHub stars
- 42
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
- 100 / 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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