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runtsang

Repository-level view of 21 collected skills across 1 GitHub repositories, including approximate occupation coverage.

skills collected
21
repositories
1
occupation fields
4
updated
2026-04-01
repository explorer

Repositories and representative skills

#001
RebuttalStudio
21 skills1952updated 2026-04-01
100% of creator
skills
Computer Science Teachers, Postsecondary

Multi-stage rebuttal analysis skill for RebuttalStudio. Use when organizing reviewer comments into stage-specific conference workflows, including stage1 breakdown, stage2 refinement, stage4 multi-round follow-up, and stage5 final remarks generation.

2026-04-01
text-condense
Editors

Condense rebuttal prose into fewer words without changing the original meaning. Use when a response block, paragraph, or selected passage is too long but all technical content, citations, and commitments must stay intact. Supports academic English.

2026-04-01
document-memory-summarize
Technical Writers

Summarize extracted paper text into concise Markdown memory for later Stage 2 and Stage 4 background use, with fixed section headings and no fabricated claims.

2026-03-27
stage1-neurips-breakdown
Teachers & Instructors, All Other

Break down full NeurIPS reviewer responses into structured rebuttal units. Use when input contains NeurIPS reviewer fields (Summary, Strengths and Weaknesses, Questions, Limitations) and numeric scores (Rating, Confidence, Quality, Clarity, Significance, Originality). Splits questions and limitations into granular response items while preserving original wording for quoted issues.

2026-03-03
stage2-neurips-refine
Technical WritersComputer Science Teachers, Postsecondary

Refine a Stage2 NeurIPS rebuttal draft into polished, reviewer-facing prose in the author's style; preserve factual grounding, optionally prepend a courteous opening phrase, and normalize tables/code/formulas into Markdown.

2026-03-03
stage1-arr-breakdown
Technical WritersComputer Science Teachers, Postsecondary

Break down full ARR (ACL Rolling Review) reviewer responses into structured rebuttal units. Use when input contains ARR reviewer fields (Paper Summary, Strengths, Weaknesses, Comments/Suggestions) and numeric scores (Confidence, Soundness, Excitement, Overall Assessment, Reproducibility). Splits weaknesses and comments/suggestions into granular response items while preserving original wording for quoted issues.

2026-03-03
stage2-arr-refine
Editors

Refine a Stage2 ARR (ACL Rolling Review) rebuttal draft into polished, reviewer-facing prose in the author's style; preserve factual grounding, optionally prepend a courteous opening phrase, and normalize tables/code/formulas into Markdown.

2026-03-03
stage1-iclr-breakdown
Computer Science Teachers, Postsecondary

Break down full ICLR reviewer responses into structured rebuttal units. Use when input contains reviewer summary/presentation/contribution/strength/weakness/question text and the goal is to split weaknesses/questions into granular R-style response items while preserving original wording for quoted issues.

2026-03-01
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