Agent skill · Code Review & Quality

slide-excellence

Multi-agent review for research presentation slides in the sewage-house-prices project (visual, econometric fidelity, proofreading, substance). Use for comprehensive quality check before milestones.

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codecan modify filesNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill slide-excellence --agent claude-code

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

Facts
Files in the skill folder: 1
SKILL.md size: 3 KB
Bundled scripts: none
Allowed tools: ReadGrepGlobWriteTask
Path: skills/41-sticerd-eee-sewage-econometrics-check/skills/slide-excellence/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

# Slide Excellence Review Run a comprehensive multi-dimensional review of research presentation slides. Multiple agents analyze the file independently, then results are synthesized. ## Steps ### 1. Identify the File Parse `$ARGUMENTS` for the filename. Resolve path in `docs/conferences/`. ### 2. Run Review Agents in Parallel **Agent 1: Visual Audit** (slide-auditor) - Overflow, font consistency, b

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About this skill
What does the slide-excellence skill do?

Multi-agent review for research presentation slides in the sewage-house-prices project (visual, econometric fidelity, proofreading, substance). Use for comprehensive quality check before milestones.

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill slide-excellence --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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