/aaai-writing-style
Use when revising an AAAI manuscript for broad-AI-audience fit, a first-page contribution statement legible to non-specialist Phase-1 reviewers, two-column readability, concise novelty claims, reproducibility-checklist alignment, hedged limitations and ethics, and policy-aware
$ npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill aaai-writing-style --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/aaai-writing-style
Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when revising an AAAI manuscript for broad-AI-audience fit, a first-page contribution statement legible to non-specialist Phase-1 reviewers, two-column readability, concise novelty claims, reproducibility-checklist alignment, hedged limitations and ethics, and policy-aware
SKILL.md
aaai-writing-style.SKILL.mdname: aaai-writing-style
description: Use when revising an AAAI manuscript for broad-AI-audience fit, a first-page contribution statement legible to non-specialist Phase-1 reviewers, two-column readability, concise novelty claims, reproducibility-checklist alignment, hedged limitations and ethics, and policy-aware framing of AI-system and capability claims.
AAAI Writing Style
Use this to make a technically sound draft readable to a broad AI program committee. AAAI rewards clear AI contribution, not only subfield-specific benchmark wins.
AAAI framing
- State the AI problem, the new capability or insight, and the evidence in the first page.
- Make clear whether the contribution is method, theory, system, benchmark, dataset, evaluation,
human-AI interaction, social impact, or alignment.
- Explain why the result matters outside a single dataset or implementation.
- Keep claims aligned with the reproducibility checklist and supplementary evidence.
- Discuss limitations and ethical considerations when the method affects people, safety, privacy,
fairness, security, or social impact.
Two-column readability
- Use figures and tables as decision aids, not decoration.
- Keep notation lightweight and define it near first use.
- Use compact related-work contrasts instead of long literature catalogues.
- Make the Phase 1 summary easy: problem, method, evidence, limitation, checklist compliance.
- Avoid unsupported "general intelligence", "human-level", or "safe" claims.
Reading the paper as a Phase-1 reviewer
A non-specialist on AAAI's broad committee gives the first page a few minutes and decides whether the paper is worth deeper reading. Write so that a planning or KR reviewer can summarize your learning contribution, and vice versa. Audit the opening against what that reader needs to extract fast.
| First-page question | Reviewer extracts | Failure symptom | | --- | --- | --- | | What is the problem | one AI task statement | jargon with no anchor | | What is new | the single contribution | a list, no headline | | Why believe it | evidence in one line | "see Section 6" only | | What are the limits | scope and caveat | silence or overclaim |
Phrasing fixes that survive AAAI review
- Replace "we achieve state of the art" with the specific delta and the setting it holds in.
- Replace bare "safe" or "human-level" with a measured, scoped statement the evidence supports.
- Replace a long related-work catalogue with two or three sharp contrasts a non-specialist can follow.
- Tie every strong claim back to a checklist answer so rigor and prose agree.
Worked vignette
A multi-agent paper opens with three paragraphs of game-theory notation before naming its contribution. A vision reviewer cannot find the AI claim and is likely to stop. The fix rewrites sentence one as the problem, sentence two as the new coordination mechanism, sentence three as the one-line evidence, and a final clause scoping the result to the studied setting, all on page one.
Output format
[AAAI fit sentence] <one sentence>
[Contribution type] method / theory / system / benchmark / dataset / evaluation / social impact
[First-page fixes] <problem, method, evidence, limitation>
[Checklist alignment] pass / needs revision
[Overclaim risks] <claims to narrow or evidence to add>
Read more
name: aaai-writing-style description: Use when revising an AAAI manuscript for broad-AI-audience fit, a first-page contribution statement legible to non-specialist Phase-1 reviewers, two-column readability, concise novelty claims, reproducibility-checklist alignment, hedged limitations and ethics, and policy-aware framing of AI-system and capability claims.
AAAI Writing Style
Use this to make a technically sound draft readable to a broad AI program committee. AAAI rewards clear AI contribution, not only subfield-specific benchmark wins.
AAAI framing
- State the AI problem, the new capability or insight, and the evidence in the first page.
- Make clear whether the contribution is method, theory, system, benchmark, dataset, evaluation,
human-AI interaction, social impact, or alignment.
- Explain why the result matters outside a single dataset or implementation.
- Keep claims aligned with the reproducibility checklist and supplementary evidence.
- Discuss limitations and ethical considerations when the method affects people, safety, privacy,
fairness, security, or social impact.
Two-column readability
- Use figures and tables as decision aids, not decoration.
- Keep notation lightweight and define it near first use.
- Use compact related-work contrasts instead of long literature catalogues.
- Make the Phase 1 summary easy: problem, method, evidence, limitation, checklist compliance.
- Avoid unsupported "general intelligence", "human-level", or "safe" claims.
Reading the paper as a Phase-1 reviewer
A non-specialist on AAAI's broad committee gives the first page a few minutes and decides whether the paper is worth deeper reading. Write so that a planning or KR reviewer can summarize your learning contribution, and vice versa. Audit the opening against what that reader needs to extract fast.
| First-page question | Reviewer extracts | Failure symptom | | --- | --- | --- | | What is the problem | one AI task statement | jargon with no anchor | | What is new | the single contribution | a list, no headline | | Why believe it | evidence in one line | "see Section 6" only | | What are the limits | scope and caveat | silence or overclaim |
Phrasing fixes that survive AAAI review
- Replace "we achieve state of the art" with the specific delta and the setting it holds in.
- Replace bare "safe" or "human-level" with a measured, scoped statement the evidence supports.
- Replace a long related-work catalogue with two or three sharp contrasts a non-specialist can follow.
- Tie every strong claim back to a checklist answer so rigor and prose agree.
Worked vignette
A multi-agent paper opens with three paragraphs of game-theory notation before naming its contribution. A vision reviewer cannot find the AI claim and is likely to stop. The fix rewrites sentence one as the problem, sentence two as the new coordination mechanism, sentence three as the one-line evidence, and a final clause scoping the result to the studied setting, all on page one.
Output format
[AAAI fit sentence] <one sentence> [Contribution type] method / theory / system / benchmark / dataset / evaluation / social impact [First-page fixes] <problem, method, evidence, limitation> [Checklist alignment] pass / needs revision [Overclaim risks] <claims to narrow or evidence to add>
Stanford REAP × CoPaper.AI · 由斯坦福实证方法论团队精选与维护 访问 copaper.ai 微信:CoPaper.AI 按 11 个主流学科板块覆盖 经管与商科 社会科学 人文学科 数学与物理科学 生命科学 医学与健康 工程与技术 计算机科学与 AI 体育科学 点击任一学科名可跳转到对应说明;每类下的代表子领域在正文总览中完整列出。下方封面墙按 venue 导航,完整分类见覆盖一览。 🧭 布局指南 · 📚 Skill Pack 一览 · ⚡ 如何使用 · 🧪 自动实证
Other skills on awesome-journal-skills.
- /aaai-artifact-evaluation
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
Open skill - /aaai-author-response
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round
Open skill - /aaai-camera-ready
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and
Open skill - /aaai-experiments
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and
Open skill - /aaai-related-work
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a
Open skill - /aaai-reproducibility
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that
Open skill

