Agent skill

Expecon Topic Selection

by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills

A skill your agent uses when deciding whether a question is a method-defined fit for an Experimental Economics (ExpEcon) manuscript and which treatment contrast to build it around.

MITAuto-check passedResearch & Science

Install Expecon Topic Selection

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill expecon-topic-selection -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills expecon-topic-selection --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Experimental-Economics-Skills/skills/expecon-topic-selection .claude/skills/expecon-topic-selection && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
expecon-topic-selection
GitHub stars
1.2k
Token cost
~1.9k tokens
SKILL.md length
958 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when deciding whether a question is a method-defined fit for an Experimental Economics (ExpEcon) manuscript and which treatment contrast to build it around.

  • Works in 3 steps: Is the object causal and behavioral? The… → Is the design the contribution, or… → Can it pass the two gates from day one?…
  • Tasks that involve Citation management
  • SKILL.md covers When to trigger, The fit decision: method…, Choosing the treatment… and Sibling boundary — pick the…, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Expecon Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. 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.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Citation management. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的… The licence is MIT.

When your agent uses it

  • Tasks that involve Citation management

Example prompts

  • “/expecon-topic-selection”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Is the object causal and behavioral? The unit of contribution is a treatment effect produced by experimental control, not an observed…
  2. Is the design the contribution, or merely a delivery vehicle? Papers that win at ExpEcon either (a) build a novel, decisive treatment…
  3. Can it pass the two gates from day one? Real salient incentives and the no-deception norm are not editorial preferences; they are entry…

What it can do on your machine

Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Expecon Topic Selection loads about 1.9k tokens when it runs. Until then it costs about 63 tokens; SKILL.md has 958 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~63
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 958 words, ~1,899 tokens.

Download SKILL.mdSave it as .claude/skills/expecon-topic-selection/SKILL.md (or your agent's skills folder).
name
expecon-topic-selection
description
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.

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 contribution, or merely a delivery vehicle? Papers that win at ExpEcon either (a) build a novel, decisive treatment contrast that prior work could not run, or (b) advance the methodology of experimentation (a better elicitation, a control that removes a confound, evidence on how a procedure biases results). A standard dictator game with a new label rarely clears the bar.
  3. Can it pass the two gates from day one? Real salient incentives and the no-deception norm are not editorial preferences; they are entry conditions. If the question can only be answered by deceiving subjects or with hypothetical stakes, redesign or send it elsewhere.

Choosing the treatment contrast (this is where the paper is won)

The center of an ExpEcon paper is the minimal pair: two conditions identical except for the one thing your hypothesis is about. Spend your design budget here.

  • Strip the contrast to a single manipulated dimension; a treatment that changes payoffs and framing and matching identifies nothing.
  • Pre-commit to the primary outcome and primary comparison in a pre-analysis plan (AEA RCT Registry / OSF / AsPredicted). For high-stakes or surprising claims, consider a Registered Report: in-principle acceptance before data collection insulates a clean null from publication bias and is increasingly welcomed in the ESA ecosystem (检索于 2026-06;以官网为准).
  • Decide matching (partner vs. stranger), information, and one-shot vs. repeated now — these are identification choices, not implementation details.

Sibling boundary — pick the right home deliberately

VenueWhat it rewardsSend there instead when…
JEBObroad behavioral/organizational questions, method-agnosticthe topic, not the design, is the contribution; you need deception
GEBgame-theoretic theorythe experiment merely illustrates a theorem
AEJ: Microapplied micro where an experiment supports a wider claimthe headline is an economic phenomenon, the experiment one leg
JESAshort-format ESA work: replications, null results, software, commentsthe paper is a brief note, not a full design paper

Deciding the experiment type (it changes everything downstream)

The same question can be a lab, lab-in-the-field, or field experiment, and the choice fixes your later bottlenecks:

TypeBuys youCosts youChoose when
Labmaximal control, clean minimal pairs, cheap iterationexternal validity questions (often student pool)the mechanism needs tight control to isolate
Lab-in-the-fielda relevant population with much control retainedrecruitment/logistics, some control lossthe population is the point (farmers, traders, CEOs)
Fieldbehavior in situ, strong external validitypartial control, attrition, often costlierthe real-world stakes are the contribution

Lab control is your comparative advantage at this journal; do not give it up unless the population or the in-situ behavior is the contribution.

Show full SKILL.md (351 more words)Show less

Checklist

  • The contribution is stated as a treatment effect / design advance, not a topic
  • The minimal-pair contrast manipulates exactly one dimension
  • Both gates clear at the idea stage: salient incentives feasible; no deception required
  • Pre-registration / Registered Report / replication status decided before data collection
  • A one-line reason this belongs at ExpEcon and not JEBO/GEB/AEJ: Micro/JESA
  • Primary outcome and primary comparison named before any results exist
  • Experiment type (lab / lab-in-field / field) chosen for a stated reason

The "could you publish a clean null?" test

A useful litmus for ExpEcon fit: imagine your treatment effect comes out exactly zero. Is the paper still publishable? If yes — because the design is decisive, the hypotheses were pre-registered, and a null adjudicates between behavioral models — you have a true method-defined contribution. If a null would be unpublishable because the paper rests entirely on getting a "surprising positive," you are leaning on the result, not the design, and you risk a publication-bias incentive to p-hack. The flagship (and especially the Registered Report track) values designs whose answer matters either way. Build the question so the null is informative.

Anti-patterns

  • A "topic paper" with an experiment bolted on, where the design teaches nothing new
  • A treatment that varies several things at once, so no single effect is identified
  • Discovering only after data collection that the design needed deception to work
  • Choosing the journal by impact factor rather than by method fit
  • Treating a brief replication or software note as a full ExpEcon design paper (that is JESA)

Worked vignette (illustrative)

A team has "a paper on whether social media reduces cooperation." Topic-first, and unidentifiable as stated. Reframing method-first: design a repeated public-goods game where one treatment injects a between-round "feed" of (real, not fabricated — gate!) peer messages and the control does not. Now the contribution is a treatment effect of peer messaging on contributions, the minimal pair manipulates only the feed, incentives are real, no deception is needed (messages are genuine), and a pre-registered primary comparison (mean contribution, Feed vs. NoFeed, at the matching-group level) exists before any data. The vague topic became a clean ExpEcon design.

Output format

text
【Journal】Experimental Economics (ESA method flagship)
【Skill】expecon-topic-selection
【Verdict】fit / reframe / reroute
【The contribution】treatment effect or design/method advance (one sentence)
【Experiment type】lab / lab-in-field / field + reason
【Minimal-pair contrast】the single manipulated dimension
【Gate check】incentives salient? no deception? [Y/N]
【Pre-reg status】PAP / Registered Report / replication / none-yet
【Why here not sibling】JEBO/GEB/AEJ:Micro/JESA reason
【Next skill】expecon-literature-positioning

© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in Experimental-Economics-Skills/skills/expecon-topic-selection of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

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Literature Reviewneflibata-feng/MyArxiv-Agent12620 repos~5.9kAutomated safety check: NotesMIT
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Questions about Expecon Topic Selection

What does Expecon Topic Selection do?

A skill your agent uses when deciding whether a question is a method-defined fit for an Experimental Economics (ExpEcon) manuscript and which treatment contrast to build it around. Expecon Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. 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.

When should I use Expecon Topic Selection?

Expecon Topic Selection fits situations like: tasks that involve Citation management.

How do I install Expecon Topic Selection in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill expecon-topic-selection -a claude-code`. Or copy the skill folder (Experimental-Economics-Skills/skills/expecon-topic-selection in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/expecon-topic-selection in your project. Claude Code loads it when a task matches its description.

How do I install Expecon Topic Selection in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill expecon-topic-selection -a codex`. Or copy the skill folder (Experimental-Economics-Skills/skills/expecon-topic-selection in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/expecon-topic-selection in your project. Codex loads it when a task matches its description.

Can I use Expecon Topic Selection in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill expecon-topic-selection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/expecon-topic-selection, .gemini/skills/expecon-topic-selection, .github/skills/expecon-topic-selection and .opencode/skills/expecon-topic-selection in your project.

What does Expecon Topic Selection need to run?

SKILL.md names no scripts, command-line tools or credentials: Expecon Topic Selection is instructions for the agent only.

Does Expecon Topic Selection access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Expecon Topic Selection safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Expecon Topic Selection use?

Expecon Topic Selection is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Expecon Topic Selection use?

About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Expecon Topic Selection?

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Who maintains Expecon Topic Selection?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.

Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.