Is this skill meant for general developers?

While it can be used by anyone, it is most beneficial for AI researchers, data scientists, and academics preparing technical manuscripts.

What are the prerequisites for using this skill?

It requires the Sibyl Codex environment and the sibyl-heavy agent tier to perform its deep analytical tasks.

Which conferences is this skill optimized for?

The skill is specifically calibrated to match the rigor and evaluation criteria of NeurIPS and ICML (International Conference on Machine Learning).

What is Sibyl Final Critic?

Sibyl Final Critic is a specialized Claude Code skill designed to provide high-level, critical peer reviews for machine learning research papers, mimicking the standards of top-tier academic conferences.

Does it provide suggestions for improvement?

Yes, it identifies weaknesses in methodology, clarity, and argumentation, allowing researchers to address potential criticisms before formal submission.

Sibyl Final Critic

Name: Sibyl Final Critic
Author: qcai0427

byqcai0427

0•

데이터 과학 및 ML

Provides rigorous, conference-grade peer reviews for machine learning research papers targeting NeurIPS and ICML standards.

Sibyl Final Critic is a specialized AI agent within the Sibyl Codex ecosystem designed to simulate the role of a senior reviewer for top-tier machine learning conferences. By utilizing the advanced sibyl-heavy agent, it performs deep technical audits of research manuscripts, evaluating methodological soundness, experimental rigor, and contribution significance. This tool is specifically engineered to help researchers identify potential reasons for rejection and improve the overall quality of their submissions to venues like NeurIPS and ICML before the actual peer-review process begins.

주요 기능

01Deep methodological and technical audit

02Pre-submission quality assurance for AI research

03Evaluation of empirical results and clarity

040 GitHub stars

05NeurIPS and ICML standard peer review simulation

06Identification of logical gaps and weak arguments

사용 사례

01Improving the clarity and impact of academic writing

02Simulating professional peer review for ML drafts

03Identifying technical flaws before conference submission

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add qcai0427/sibyl-codex sibyl-final-critic

For use in Claude.ai and ChatGPT

주요 기능

01Deep methodological and technical audit

02Pre-submission quality assurance for AI research

03Evaluation of empirical results and clarity

040 GitHub stars

05NeurIPS and ICML standard peer review simulation

06Identification of logical gaps and weak arguments

사용 사례

01Improving the clarity and impact of academic writing

02Simulating professional peer review for ML drafts

03Identifying technical flaws before conference submission

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add qcai0427/sibyl-codex sibyl-final-critic

For use in Claude.ai and ChatGPT