Draft evidence-based CS/ML paper reviews from PDFs and venue forms.
npx skills add https://github.com/yzhao062/agent-config --skill cs-paper-review
Please help me install this Agent Skill. Skill: cs-paper-review Source: https://github.com/yzhao062/agent-config/tree/main/reference-skills/cs-paper-review Command: npx skills add https://github.com/yzhao062/agent-config --skill cs-paper-review
Draft grounded CS/ML reviews for research papers using the provided PDF, extracted text, venue form, and user notes, ensuring evidence-based evaluation.
Draft a grounded CS/ML paper review using the provided PDF, extracted text, venue form, and user notes.
High-intent search queries and answers about installing and using this skill.
To draft a grounded CS/ML paper review, the Skill extracts text from the provided PDF and user notes, verifying all technical claims strictly against these source materials to produce an evidence-based evaluation.
Yes, you can generate a peer review tailored for ML venues like NeurIPS, ICML, or IJCAI. The Skill adapts its structured evaluation, author questions, and ethics considerations to fit the specific venue form fields you provide.
Evidence-based peer review validates paper claims against extracted source content. The Skill applies rigorous evidence gathering to flag prompt-injection attempts or integrity concerns, ensuring a clear, defendable evaluation of the CS/ML research.
You generate author-facing questions by supplying the paper PDF, extracted text, and user notes. The Skill drafts a technically grounded evaluation that surfaces relevant, targeted questions for the authors based on the verified content.
You need to provide the paper PDF at minimum. Supplying extracted text, venue form fields, and user notes allows the Skill to draft a more accurate, venue-specific review with rigorous evidence gathering and validated claims.
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