AGENT SKILL
paper.rate
Rate an academic paper from 1 to 5 by page length, affiliation, citations
使用场景资料检索与研究
- License 许可
- Apache-2.0
- 最近更新
- 2026-11-02
- Stars
- ★ 0
- Forks
- 1
01 前言 Front Matter
- model
- sonnet
- description
- Rate an academic paper from 1 to 5 by page length, affiliation, citations
03 SKILL.md 正文
Goal
- Rate the passed paper from 1 (low) to 5 (best) using its page length, the affiliation of its authors, and its number of citations
- Follow the rules in
.claude/skills/paper.rules.md,# Paper Rating
Workflow
Get the Paper
- Use the PDF passed by the user
- If the input is a URL, an arXiv ID, or a DOI, download only the PDF with
download_academic_paper_to_md.py --input <INPUT> --clear_actions --action download
Collect the Signals
- Count the pages of the PDF
- Read the affiliations of all the authors on the first page
- Look up the citation count in Semantic Scholar for the DOI or the arXiv ID, and note the date
- Do not use memory for any of these values
Rate
- Score each signal and compute the rating with the tables in
.claude/skills/paper.rules.md
Write the Rating File
- Save
<BASE>.rating.mdnext to the paper, where<BASE>is the name of the PDF without.pdf - Follow the template
.claude/templates/paper_rating.template.md - Report the rating and the three scores to the user
Constraints
- Use whole numbers only
- If a signal cannot be found, write
unknownand leave it out of the mean
Verification
- [ ] The rating is an integer from 1 to 5
- [ ] Each signal has a value and a score
- [ ] The citation count has a source and a date
- [ ] The rating equals the mean of the known scores, rounded half up
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