Analyze LaTeX research papers and generate expert CV professor feedback.
npx skills add https://github.com/mobled37/claude-labs --skill ask-professor
Please help me install this Agent Skill. Skill: ask-professor Source: https://github.com/mobled37/claude-labs/tree/main/skills/ask-professor Command: npx skills add https://github.com/mobled37/claude-labs --skill ask-professor
This skill provides instant access to expert critique from a senior CV professor who has read your paper, helping you identify and fix tone, argument gaps, and strategic positioning before submission.
Provide the path to your paper project and an optional question to start a Q&A session with a senior CV professor.
High-intent search queries and answers about installing and using this skill.
You can get expert feedback by running an interactive Q&A session that reviews your LaTeX sources and bibliography. The session provides actionable critique on tone, argument consistency, and experimental rigor from a senior CV professor.
Yes, you can review your LaTeX manuscript for CVPR or ICCV submission. The tool detects venue requirements and strategic positioning across sections, surfacing potential reviewer concerns and recommended experiments to improve your paper.
To start a Q&A session, provide the path to your paper project along with an optional question. The system reads all LaTeX sources and bibliographies to detect root structure and generates concrete suggestions for experimental rigor.
The best way to check tone and argument consistency is through a comprehensive review session that analyzes your manuscript sections. It identifies gaps in writing quality and argument consistency, providing real-time guidance and actionable feedback.
No specific dependencies or components are required to use this paper review tool. You simply need to provide the file path to your paper project to initiate the expert critique and strategic positioning analysis.
The feedback focuses on strategic positioning to ensure your paper meets venue requirements and addresses potential reviewer concerns. By reading all LaTeX sources, it evaluates the root structure to generate actionable, targeted suggestions.
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