aspi6246

aspi6246 / Claude-Code-Skills-for-Academics

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A collection of Skills for academics.

37
6
100% credibility
Found Apr 08, 2026 at 37 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A personal collection of instructions and a slide-checking tool designed to enhance an AI coding assistant for empirical finance academics, covering R workflows, LaTeX presentations, code audits, and paper reviews.

How It Works

1
🔍 Discover AI Research Skills

You find this collection of helpful guides that turn your AI coding assistant into an expert for university finance research tasks.

2
đź“Ą Add Skills to Your AI

Download the pack and slip it into your AI helper's special skills spot so it's all set up and ready.

3
đź“‹ Pick a Skill to Use

Choose from options like finance data coding, making teaching slides, checking presentations, or reviewing research papers.

4
🔧 Check Your Slides

Use the slide checker to build your presentation, catch any glitches, and get pictures of every slide for a close look.

5
đź“Š Spot and Fix Issues

Review the easy list of errors, layout problems, and slide images to quickly make everything perfect.

âś… Flawless Research Work

Your presentations shine without errors, your code is solid, and your AI boosts your academic workflow beautifully.

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AI-Generated Review

What is Claude-Code-Skills-for-Academics?

This claude code skills github repo from aspi6246 delivers a curated claude skills collection for academics, especially in empirical finance research. It provides drop-in Markdown skills for Claude Code—Anthropic's coding companion—covering R pipelines with data.table and fixest, LaTeX Beamer slide generation in house styles, code audits with data safeguards, dataset profiling, and paper editing protocols. Users clone it straight into Claude's skills directory for instant workflow boosts, plus a Python CLI that compiles Beamer TeX files, parses logs for errors and layout issues, renders slides as PNGs, and outputs JSON diagnostics.

Why is it gaining traction?

Unlike generic anthropic github claude code skills or github skills collections, this stands out with academia-specific prompts that nail research rituals like causal inference setups and seven-step paper reviews—saving hours on repetitive tasks. The beamer-check tool hooks users by automating the compile-inspect-fix loop, spotting overfull boxes and missing files without manual log dives. Early adopters praise its plain Markdown simplicity for quick skill tweaks and GitHub-backed updates.

Who should use this?

Empirical finance researchers grinding panel data in R, profs crafting Beamer decks for lectures, or PhD students auditing code before submissions. Ideal if you're in UTS-style LaTeX workflows or need structured paper reviews, but skip if your stack is pure ML or non-academic.

Verdict

With 37 stars and a 1.0% credibility score, it's an early-stage github claude code skills repo—light on tests but solid docs and focused utility. Worth forking for finance academics using Claude Code; otherwise, monitor for maturity.

(182 words)

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