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ml-paper-writing
Use when drafting ML/AI papers, verifying citations, framing evidence, using LaTeX, or preparing submissions.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
メニュー
Use when drafting ML/AI papers, verifying citations, framing evidence, using LaTeX, or preparing submissions.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | ml-paper-writing |
| description | Use when drafting ML/AI papers, verifying citations, framing evidence, using LaTeX, or preparing submissions. |
| allowed-tools | Read,Write,Edit,Bash,Glob,Grep,WebSearch,WebFetch |
Use for ML/AI research papers targeting venues such as NeurIPS, ICML, ICLR, ACL, AAAI, and COLM. Be proactive when the repo, results, and contribution are clear.
Never invent citations or BibTeX. Search, verify, fetch BibTeX from DOI when possible, and mark unresolved references as placeholders.
.bib, and experiment outputs.The introduction must make the contribution legible before methods. Every experiment states the claim it tests. Baselines must be fair. Figures should be self-contained, readable, and colorblind-safe. Claim strength must match evidence.
Load citation, structure, evidence, writing, style, formatting, checklist, abstract, or reviewer references only when the current paper task needs them.
Use when copy editing, proofreading, polishing, or removing AI-sounding prose.
Use when creating Data/AI strategy, principles, roadmaps, MLOps plans, or executive docs.
Use when coaching technical leaders on conflict, burnout, cofounders, CTO transitions, or growth.
Use when writing Manning-style technical chapters, Chapter 1s, examples, callouts, or summaries.
Use when writing strategic tech posts, engineering narratives, opinion pieces, or industry analysis.