Agent skill · Data & Analytics

e3

Agent E3 - Mixed Methods Integration Specialist - Qual-Quant data integration and meta-inference. Covers joint display creation, integration strategies, and legitimation techniques.

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill e3 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 15 KB
Bundled scripts: none
Version: 12.0.1
Path: skills/25-HosungYou-Diverga/skills/e3/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,244
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

## ⛔ Prerequisites (v8.2 — MCP Enforcement) `diverga_check_prerequisites("e3")` → must return `approved: true` If not approved → AskUserQuestion for each missing checkpoint (see `.claude/references/checkpoint-templates.md`) ### Checkpoints During Execution - 🟠 CP_INTEGRATION_STRATEGY → `diverga_mark_checkpoint("CP_INTEGRATION_STRATEGY", decision, rationale)` ### Fallback (MCP unavailable) Read `.

More from Auto-Empirical-Research-Skills
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About this skill
What does the e3 skill do?

Agent E3 - Mixed Methods Integration Specialist - Qual-Quant data integration and meta-inference. Covers joint display creation, integration strategies, and legitimation techniques.

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill e3 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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