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By caidish
Guide section-by-section reviews of scientific papers from PDF or LaTeX: convert PDF to LaTeX, log issues, verify math equations, figures, and citations, then generate structured responses. Analyze images to describe content, extract data from scientific plots, figures, and experimental setups.
npx claudepluginhub caidish/cai-tools --plugin science-skillCopilot for scientific paper review. Use when reviewing a research paper (PDF/LaTeX), guiding section-by-section analysis, logging issues, and generating structured review responses.
Use when you want to analyze, describe, or extract information from an image. Handles scientific figures, plots, experimental setups, and general image Q&A.
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Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Scientific writing, citations, grants, posters, and academic career (13 skills)
Research-team agents for Claude Code: supervisor, analysis-implementer, paper-writer, figure-descriptor, reviewer, literature-curator.
Specialized research analysis agents for critical thinking, evidence verification, synthesis, and parallel paper analysis
Research integrity plugin for Claude Code — paper auditing, citation verification, experiment analysis, and methodology-first skills for academic workflows.
Academic research agents — hypothesis generation, experiment design, paper drafting, peer review simulation, and more.
Oh My Paper research harness: memory system, Codex delegation, and pipeline commands for academic research projects.
Collection of useful prompted subagents for code review, API docs, QA, and more
macOS integration - speak, send iMessages, emails, manage calendar, and display stickies
Pushover notification hooks - get notified when tasks complete or permissions are needed. Requires: python3 and psutil. Install: pip install psutil. Verify: python3 -c 'import psutil; print(psutil.__version__)'
Skills for interacting with other AI tools - Codex, Gemini CLI, and collaboration fixes
Control KLayout from AI agents via MCP — geometry, display, image overlay, visual capture, nanodevice flake detection, GDS alignment, and routing skills for chip/mask layout design
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