Agent skill

expecon-topic-selection

Use when deciding whether a question is a method-defined fit for an Experimental Economics (ExpEcon) manuscript and which treatment contrast to build it around. Frames the fit decision; it does not invent results or citations.

brycew6m4,252★ · +31/wk · 3 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill expecon-topic-selection --agent claude-code

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

Facts
Files in the skill folder: 1
SKILL.md size: 7 KB
Bundled scripts: none
Path: Experimental-Economics-Skills/skills/expecon-topic-selection/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 984 · +31 this week
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

# Topic Selection (expecon-topic-selection) ## When to trigger - You have an interesting economic question but are unsure an experiment is the right tool — or whether *this* journal is the right home for it - The draft reads topic-first ("a paper about charitable giving") rather than method-first ("a design that isolates warm-glow from social-image motives") - You must decide *before* collecting data whether to pre-register, run a Registered Report, or pursue a replication - The paper could plausibly land at JEBO, GEB, AEJ: Micro, or JESA and you need to pick deliberately ## The fit decision: method first, topic second Experimental Economics is the **ESA method flagship**. The editors do not ask "is this topic important?" so much as "is this **the cleanest experiment** that could answer this question, and does the design *itself* teach the field something?" Three questions decide fit: 1. **Is the object causal and behavioral?** The unit of contribution is a **treatment effect produced by experimental control**, not an observed correlation or a calibrated structural object. If your answer lives in field-survey data, you are at an applied journal, not here. 2. **Is the design the con

What's inside
Steps it walks through
  1. When to trigger
  2. The fit decision: method first, topic second
  3. Choosing the treatment contrast (this is where the paper is won)
  4. Sibling boundary — pick the right home deliberately
  5. Deciding the experiment type (it changes everything downstream)
  6. Checklist
  7. The "could you publish a clean null?" test
  8. Anti-patterns
  9. Worked vignette (illustrative)
  10. Output format
More from Awesome-Journal-Skills
All skills →
About this skill
What does the expecon-topic-selection skill do?

Use when deciding whether a question is a method-defined fit for an Experimental Economics (ExpEcon) manuscript and which treatment contrast to build it around. Frames the fit decision; it does not invent results or citations.

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill expecon-topic-selection --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/Awesome-Journal-Skills, a repository with 984 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.

Keep going