aaai26-ai-review
by 聊言青
A multi-stage, evidence-grounded academic review agent modeled on the AAAI-26 AI Review Pilot research.
- Conduct pre-submission critiques for research paper drafts
- Identify missing baselines and related work in empirical AI papers
- Verify notation consistency and mathematical correctness in technical sections
Free
One-time purchase · Own forever
See it in action
Strengths: - Novel application of Latent SDEs to time-series forecasting. Weaknesses: - Major: Missing comparison with [Source B] in Table 2. - Major: Theorem 3.1 assumes Lipschitz continuity without proof. - Minor: Notational conflict between Eq. 4 and Eq. 7 regarding the 'lambda' term.
aaai26-ai-review
by 聊言青
A multi-stage, evidence-grounded academic review agent modeled on the AAAI-26 AI Review Pilot research.
Free
One-time purchase · Own forever
⚡ Also available via Agensi MCP — your AI agent can load this skill on demand via MCP. Learn more →
Included in download
- Downloadable skill package
- Instant install
See it in action
Strengths: - Novel application of Latent SDEs to time-series forecasting. Weaknesses: - Major: Missing comparison with [Source B] in Table 2. - Major: Theorem 3.1 assumes Lipschitz continuity without proof. - Minor: Notational conflict between Eq. 4 and Eq. 7 regarding the 'lambda' term.
About This Skill
Generate high-quality AI-assisted peer reviews modeled on the publicly described logic of the AAAI-26 AI Review Pilot. This skill implements a multi-stage review pipeline: it decomposes the paper into specialized analysis dimensions (contributions, methodology, experiments, presentation), synthesizes findings, self-critiques the draft for unsupported claims, and runs a final quality check for anonymity leaks and citation hallucinations. Output follows a structured format (Synopsis, Summary of Review, Strengths, Weaknesses with Major/Minor labels, References) — no accept/reject verdict by default, mirroring the AAAI-26 design philosophy of AI-as-assistance rather than AI-as-decision-maker. Compatible with PDF input. Works for any venue: AAAI, NeurIPS, ICML, ACL, CVPR, and more.
📖 Learn more: Best Code Review Skills for Claude Code →
Use Cases
- Conduct pre-submission critiques for research paper drafts
- Identify missing baselines and related work in empirical AI papers
- Verify notation consistency and mathematical correctness in technical sections
- Generate objective second opinions for conference program committees
How to Install
unzip aaai26-ai-review.zip -d ~/.claude/skills/Reviews
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