brycewang-stanford

brycewang-stanford / Awesome-Agent-Skills-for-Empirical-Research

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🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文，并支持用户上传 Skills。

copaper.ai academic-research agent-skills ai-agent awesome-list communication
16
8
100% credibility
Found Apr 08, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Stata
AI Summary

A curated collection of GitHub repositories containing AI agent skills for empirical research workflows across social sciences, organized by stages from topic ideation to peer review.

How It Works

1
🔍 Discover the skill collection

You search online for AI helpers for your research and find this big list of tools organized by steps like picking topics or analyzing data.

2
📖 Pick tools for your stage

Look at the quick guide matching your current work, like data cleaning or writing results, and choose ready-made helpers that fit.

3
⭐ Grab a full toolkit

Select a complete set covering idea to paper, or pick ones for your exact need like checking causes and effects.

4
Choose your path
⚡
Quick single tool

Add one helper for your current task and get instant speedup.

🏗️
Full research team

Set up a group of tools that handle the whole project from start to finish.

5
🚀 Connect to your AI helper

Copy the tools into your AI chat program so it knows how to use them automatically.

6
💡 Run your analysis

Tell your AI what to do, like 'check trends before treatment,' and it follows the full expert steps without you reminding.

🎉 Finish faster and better

Your research flows smoothly with all checks done, ready for writing or sharing results confidently.

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AI-Generated Review

What is Awesome-Agent-Skills-for-Empirical-Research?

This GitHub curated list assembles over 23,000 agent skills from 119 repos into an awesome curated collection for empirical research across 8 social science disciplines like economics and sociology. It organizes them by workflow stages—from topic ideation and lit review to causal inference, paper writing, and replication—letting researchers grab ready-made AI prompts for full analyses like DID or IV. Users get a one-stop directory plus one-click integrations for tools like CoPaper.AI, which spits out reproducible papers in 20 minutes using built-in econometric skills.

Why is it gaining traction?

Unlike scattered GitHub repos, this stands out as a centralized, opinionated curated collection that maps skills to exact research pain points, with quick lookups by stage and comprehensive suites for econ or public health. Developers notice the multi-agent systems and MCP servers for databases like OpenAlex or FRED, slashing setup time for lit searches or data pulls. The bilingual docs and PR welcome policy keep it fresh as a go-to github curated list.

Who should use this?

Empirical social scientists running causal models in Stata, R, or Python; PhD students automating DID robustness checks or grant writing; policy analysts needing quick lit reviews across disciplines. Ideal for anyone tired of prompting LLMs step-by-step for parallel trends plots or PSM balancing.

Verdict

Solid starting point for agent-driven research despite low maturity—16 stars and 1.0% credibility score signal it's early days with thin testing. Grab it if you're in social sciences; skip for production unless you vet the aggregated skills yourself. (187 words)

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