paper-relevance-scorer

paper-relevance-scorer is a Literature review & citations skill for AI agents, published by AkaliKong in the PaperClaw repository on GitHub. Skillspace rates paper-relevance-scorer C (71/100) and it passed the safety scan; the rating is based on static analysis only.

对搜索到的论文进行相关性评分（0-10分），采用三步式 Agent 编排：脚本准备上下文→Agent LLM 打分→脚本后处理。当用户说"给这些论文打分"、"评估论文相关性"时触发。

Grade
C
Quality
71 / 100
Safety
Passed
GitHub stars
22

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.

View source on GitHubAkaliKong/PaperClaw

Our review

Architecture
94 / 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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