Orchestrate multi-agent academic review workflows for computer vision LaTeX papers.
npx skills add https://github.com/mobled37/claude-labs --skill cv-lab
Please help me install this Agent Skill. Skill: cv-lab Source: https://github.com/mobled37/claude-labs/tree/main/skills/cv-lab Command: npx skills add https://github.com/mobled37/claude-labs --skill cv-lab
This Skill automates the end-to-end academic review workflow for computer vision LaTeX papers, coordinating multiple reviewer roles to streamline feedback and revisions.
Provide the path to your LaTeX project directory and optional threshold and max-rounds parameters to start the review pipeline.
High-intent search queries and answers about installing and using this skill.
You can automate the academic review workflow for computer vision LaTeX papers by orchestrating Professor, Peer, and Official Reviewer roles to produce structured evaluations, color-coded revisions, and a final decision gate.
Yes, inline comments and revision planning are generated directly within your LaTeX paper project, applying document discovery to main.tex, bib, and figures to coordinate phase-based execution and round-based scoring.
The best way to coordinate academic paper revisions is through a multi-agent orchestration workflow that schedules Professor, Peer, and Official Reviewer evaluations sequentially to satisfy end-to-end reproducibility.
Yes, you can configure the academic review workflow by providing optional threshold and max-rounds parameters alongside your LaTeX project directory path to control the revision pipeline depth.
A final decision gate is needed when finalizing conference submissions or supervising student papers, ensuring all Professor, Peer, and Official Reviewer feedback meets the required round-based scoring threshold before approval.
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