Review research code for reproducibility and quality, extract the paper's main empirical claims, compare paper to code, and write a constructive markdown report. Designed for quantitative marketing / economics projects with LaTeX papers and R or Python code.
/plugin marketplace add ericluo04/claude-academic-workflow
The exact command may vary by repository. Check the README on GitHub.
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Automates browser interactions with persistent page state. Use for navigating websites, filling forms, taking screenshots, extracting web data, testing web apps, or automating browser workflows.
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to
Use when you need to ask questions about a codebase or understand code using a knowledge graph.
Launch the interactive web dashboard to visualize a codebase's knowledge graph.
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Source. This skill is adapted from
claesbackman/AI-research-feedback. The 5-phase design (Discovery → Paper Analysis → Parallel Code Review → Synthesis → Report) is Claes Bäckman's; this fork tunes the language stack to R / Python (no Stata) and the project conventions to quantitative-marketing layouts.
Review a research project's paper and code for reproducibility, code quality, and paper-code alignment. Be co
[Description truncada. Veja o README completo no GitHub.]
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