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/ai-augmented-economist

Integrate AI tools into economic research, teaching, and policy analysis with attention to privacy and reproducibility.

@brycewang-stanfordbrycewang-stanford@brycewang-stanford
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auto-empirical-research-skills
3.3k200 skills146 agents
Install
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill ai-augmented-economist --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/ai-augmented-economist

Context preview

The summary Claude sees to decide when to auto-load this skill.

Integrate AI tools into economic research, teaching, and policy analysis with attention to privacy and reproducibility.

SKILL.md

ai-augmented-economist.SKILL.md
name: ai-augmented-economist
description: Integrate AI tools into economic research, teaching, and policy analysis with attention to privacy and reproducibility.
owner: Vera / Personal
tags: [AI, research, teaching]
triggers: ["use AI tools","automate analysis","AI in economics"]
inputs:
  - name: project_context
    type: string
    required: false
outputs:
  - name: integration_plan
    type: document
  - name: data_pipeline_design
    type: document
examples:
  - prompt: |
      Propose an AI integration plan for a small research team analyzing childcare data.
    expected: |
      Tool choices, privacy safeguards, reproducible pipeline, and SLA for model updates.
guardrails: |
  Do not upload personally identifying data to external models; document training data provenance.

Purpose

Provide a stepwise approach to choose AI tools, build secure data pipelines, and apply AI methods responsibly in economics work.

Workflow

1. Assess tasks suitable for AI augmentation 2. Select tools considering privacy and licensing 3. Build reproducible data pipelines and artifact tracking 4. Validate outputs against domain knowledge and econometric checks 5. Monitor models and document assumptions

Read it on GitHub ↗
Ships withauto-empirical-research-skills

📌 文档结构（2026-07-22 起）： 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md（扩展正文，总表行内的 → 直接跳转到对应锚点）。 English version: README-en.md · 中文扩展正文：docs/CONTENT_ZH.md · README-zh-CN.md 已弃用（重定向占位） 🌐 语言: English |

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Repo: brycewang-stanford/Auto-Empirical-Research-Skills

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