Install
$ agentstack add skill-brycewang-stanford-awesome-journal-skills-aaai-writing-style ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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]
[Contribution type] method / theory / system / benchmark / dataset / evaluation / social impact
[First-page fixes]
[Checklist alignment] pass / needs revision
[Overclaim risks]
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: brycewang-stanford
- Source: brycewang-stanford/Awesome-Journal-Skills
- License: MIT
- Homepage: https://www.copaper.ai
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.