A skill your agent uses when responding to a revise-and-resubmit or referee report for an Experimental Economics (ExpEcon) manuscript — including when a referee demands a new treatment, more…

MITAuto-check passedResearch & Science

Install Expecon Rebuttal

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

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills expecon-rebuttal --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-rebuttal .claude/skills/expecon-rebuttal && 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-rebuttal
GitHub stars
1.2k
Token cost
~2.1k tokens
SKILL.md length
1,067 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when responding to a revise-and-resubmit or referee report for an Experimental Economics (ExpEcon) manuscript — including when a referee demands a new treatment, more…

  • Works in 4 steps: Triage every comment into: (a) new data… → Address the gate concerns first and… → For each new-data request, decide and… → …
  • Responding to a revise-and-resubmit
  • SKILL.md covers When to trigger, The ExpEcon revision reality:…, Triaging the common ExpEcon… and Writing the response letter, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Expecon Rebuttal is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when responding to a revise-and-resubmit or referee report for an Experimental Economics (ExpEcon) manuscript — including when a referee demands a new treatment, more sessions, or raises a deception/power concern. Plans the response; it does not run the new analysis.

Its SKILL.md is about 2.1k 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 Peer review. 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

  • Responding to a revise-and-resubmit
  • Referee report for an Experimental Economics (ExpEcon) manuscript — including when a referee demands a new treatment
  • Raises a deception/power concern

Example prompts

  • “/expecon-rebuttal”

Workflow steps

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

  1. Triage every comment into: (a) new data needed (new treatment / more sessions), (b) re-analysis (correct inference unit, MHT correction…
  2. Address the gate concerns first and decisively. A deception worry is existential: either prove the procedure is not deception under the…
  3. For each new-data request, decide and justify. Run it if it sharpens identification or power; if not, explain precisely why the existing…
  4. Re-deposit the package. New sessions mean updated data, instructions, and z-Tree/oTree code in the repository; keep the replication…

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 Rebuttal loads about 2.1k tokens when it runs. Until then it costs about 72 tokens; SKILL.md has 1,067 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~72
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

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). 1,067 words, ~2,080 tokens.

Download SKILL.mdSave it as .claude/skills/expecon-rebuttal/SKILL.md (or your agent's skills folder).
name
expecon-rebuttal
description
Use when responding to a revise-and-resubmit or referee report for an Experimental Economics (ExpEcon) manuscript — including when a referee demands a new treatment, more sessions, or raises a deception/power concern. Plans the response; it does not run the new analysis.

Rebuttal Strategy (expecon-rebuttal)

When to trigger

  • An R&R or rejection arrived and you must decide what to concede, contest, or re-run
  • A referee asks for a new treatment or more sessions — the costliest and most common ExpEcon request
  • A reviewer raised a deception or power/inference-unit concern that could be decisive
  • Two referees disagree, or the two editors' priorities differ, and you need a coherent plan

The ExpEcon revision reality: new data is on the table

Unlike journals where revisions are textual, an ExpEcon R&R often requires collecting new data — an added control treatment, more matching groups for power, or a robustness condition. Plan the response around that fact.

  1. Triage every comment into: (a) new data needed (new treatment / more sessions), (b) re-analysis (correct inference unit, MHT correction, new test), (c) clarification (already in the paper, surface it), (d) respectful disagreement (with evidence). Most letters are mostly (b)–(c); isolate the (a) items because they set the timeline and budget.
  2. Address the gate concerns first and decisively. A deception worry is existential: either prove the procedure is not deception under the ESA definition, or re-run without it — there is no middle path. A power/unit concern: re-analyze at the session/matching-group level and report MDE; if truly underpowered, run additional sessions rather than argue.
  3. For each new-data request, decide and justify. Run it if it sharpens identification or power; if not, explain precisely why the existing design already answers the question (and offer a cheaper analysis that addresses the underlying worry). Never silently ignore a request for a treatment.
  4. Re-deposit the package. New sessions mean updated data, instructions, and z-Tree/oTree code in the repository; keep the replication deposit in sync with the revised paper.

Triaging the common ExpEcon requests

Referee requestDefault responseCost
"Add a control treatment that isolates X"usually run it — it is the cleanest answernew sessions
"Underpowered / wrong inference unit"re-analyze at group level; add sessions if MDE not metre-analysis ± data
"Could be deception / demand effects"prove non-deception per ESA definition, or re-runpossibly fatal
"Comprehension/confusion confound"report pass rates; re-analyze excluding failersre-analysis
"Why not JEBO/GEB?"sharpen the methods contribution in framingtext only
"More structural estimation"add if it identifies a parameter; else decline with reasonanalysis

Writing the response letter

  • Point-by-point, quote-then-respond. Reproduce each comment, then state the change, the location (section/table/figure), and the new result. Editors and referees verify against the manuscript.
  • Lead with what you did, not why the referee was wrong. Even when contesting, open with the action taken or the evidence, in a collegial register.
  • Report new numbers honestly. If a new treatment weakened the effect, say so and interpret it; an experimentalist audience values the clean result over the convenient one.
  • Separate primary from exploratory in everything you add, mirroring the pre-registration logic.
  • Mind the two-editor structure. Where referees conflict, address both and let the response help the editors converge; do not pick one referee and ignore the other.

Worked vignette (illustrative)

A referee says a coordination-game result "might be a demand effect — subjects guessed the hypothesis." Three moves: (1) note the abstract/neutral framing already used (no leading language — quote the instructions); (2) report the post-experiment belief question showing subjects did not infer the hypothesis; (3) if still unconvinced, add a treatment with an obfuscated cover task and show the effect persists (illustrative: 0.7 SD, unchanged). The letter leads with these three actions, not with "the referee is mistaken," and updates the instructions and data in the repository to match.

Budgeting the new-data round

An added treatment is not just bench cost — it is a timeline the editors will weigh. Before committing, estimate: sessions needed for the new arm at the group-level power you must hit, lab availability, IRB amendment time, and re-deposit effort. If a requested treatment is genuinely infeasible, say so explicitly and offer the strongest available substitute (a re-analysis, a bound, or a focused robustness condition) rather than a vague promise. Editors respond far better to "we ran 10 of the 12 sessions you asked for; here is why 12 was infeasible and what the 10 show" than to silence or hand-waving.

Show full SKILL.md (378 more words)Show less

Checklist

  • Every comment triaged: new-data / re-analysis / clarification / disagreement
  • Gate concerns (deception, incentive compatibility) resolved decisively, not argued around
  • Power/inference-unit concerns met with group-level re-analysis or additional sessions
  • Each new-treatment request is run or its omission is precisely justified
  • Response is point-by-point, quote-then-respond, with exact locations of changes
  • New results reported honestly, including any that weaken the original claim
  • Replication deposit (data, instructions, z-Tree/oTree) updated to match the revision

Keeping pre-registration credible through revision

A subtle ExpEcon trap: a referee asks for a new analysis or treatment, you run it, and your "pre-registered" framing quietly erodes because the new work was not pre-specified. Protect the distinction in the revision. Anything you add at the referee's request is, by definition, not part of the original confirmatory plan — label it as referee-requested and exploratory, and keep the original pre-registered primary test reported exactly as filed. For a substantial new treatment, consider pre-registering its analysis before collecting it, and say so in the letter. Editors trust authors who keep the confirmatory/exploratory line clean under revision pressure; blurring it to make new results look pre-planned is the fastest way to lose that trust.

Anti-patterns

  • Arguing a deception concern away instead of removing the procedure
  • Promising a treatment "in future work" when the referee asked for it now
  • Burying a weakened effect from a new treatment instead of interpreting it
  • A defensive letter that disputes referees before reporting any changes
  • Updating the manuscript but leaving the repository deposit stale
  • Satisfying one referee while ignoring the other under a two-editor decision

When the decision is reject, not R&R

A flagship reject is not the end of the experiment — the data are clean and the design is real. Triage the report for what is fixable (positioning, power, a missing control) versus fatal at this venue (a deception concern that cannot be removed, or a contribution the editors judge topical rather than methodological). If the core is sound but the contribution was read as too narrow, JESA is the natural next ESA home (replications, null results, shorter design notes). If a referee's deception read is correct, the only path is a re-designed follow-up. Do not resubmit the same paper to the flagship after a reject without a substantive change to the dimension that sank it.

Output format

text
【Journal】Experimental Economics (ESA method flagship)
【Skill】expecon-rebuttal
【Decision type】R&R / reject-resubmit / conditional accept
【Triage】new-data / re-analysis / clarification / disagreement (counts)
【Gate items】deception / incentive concerns — resolution
【New-data items】treatment/sessions to run or justified omission
【Letter form】point-by-point, quote-then-respond, locations cited? [Y/N]
【Package sync】repository updated to revision? [Y/N]
【Next step】re-run expecon-identification/robustness for new data → expecon-submission for resubmission

© 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-rebuttal of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Expecon Rebuttal next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Expecon Rebuttal compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Expecon Rebuttal this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~2.1kAutomated safety check: PassMIT
Peer Reviewspacering-net/codeg3.9k17 repos~5.9kAutomated safety check: NotesMIT
Scholar Evaluationspacering-net/codeg3.9k11 repos~3.2kAutomated safety check: PassMIT
Academic Paper Writing PipelineImbad0202/academic-research-skills51k—~16kAutomated safety check: PassCustom licence
Academic Paper ReviewerImbad0202/academic-research-skills51k—~11kAutomated safety check: PassCustom licence
Peer ReviewK-Dense-AI/claude-scientific-writer2.4k2 repos~3.1kAutomated safety check: NotesMIT

Similar skills

  • Peer Review

    spacering-net/codeg

    Structured manuscript/grant review with checklist-based evaluation.

    3.9k GitHub starsUsed in 17 repos~5.9k tokens
    Research & ScienceAuto-check: notes
  • Scholar Evaluation

    spacering-net/codeg

    Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and…

    3.9k GitHub starsUsed in 11 repos~3.2k tokens
    Research & ScienceAuto-check passed
  • Academic Paper Writing Pipeline

    Imbad0202/academic-research-skills

    Runs a 12-agent pipeline that plans, drafts, cites, reviews and formats academic papers, with modes for revision, rebuttals, abstracts and citation checks.

    51k GitHub stars~16k tokensUpdated yesterday
    Research & ScienceAuto-check passed
  • Academic Paper Reviewer

    Imbad0202/academic-research-skills

    Simulates a journal peer review of a manuscript with a five-seat reviewer panel, an editorial synthesizer and several review modes.

    51k GitHub stars~11k tokensUpdated yesterday
    Research & ScienceAuto-check passed
  • Peer Review

    K-Dense-AI/claude-scientific-writer

    Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.

    2.4k GitHub starsUsed in 2 repos~3.1k tokens
    Research & ScienceAuto-check: notes
  • Academic Research Pipeline

    Imbad0202/academic-research-skills

    Orchestrates a ten-stage academic workflow from research to finished manuscript, including integrity checks, two rounds of peer review and revision.

    51k GitHub stars~15k tokensUpdated yesterday
    Research & ScienceAuto-check passed

More from brycewang-stanford/Awesome-Journal-Skills

All 2,387 skills in this repo
  • Aaag Data Analysis

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…

    1.2k GitHub stars~1.3k tokensUpdated 14 days ago
    Auto-check passed
  • Aaag Literature Positioning

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…

    1.2k GitHub stars~1.3k tokensUpdated 14 days ago
    Auto-check passed
  • Aaag Rebuttal

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and…

    1.2k GitHub stars~1.4k tokensUpdated 14 days ago
    Auto-check passed
  • Aaag Research Design

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and…

    1.2k GitHub stars~1.4k tokensUpdated 14 days ago
    Auto-check passed
  • Aaag Review Process

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when you need to understand how the Annals of the American Association of Geographers evaluates a manuscript — double-anonymous review routed through a subject editor by…

    1.2k GitHub stars~1.3k tokensUpdated 14 days ago
    Auto-check passed
  • Aaag Submission

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when running the final pre-submission preflight for the Annals of the American Association of Geographers via ScholarOne Manuscripts — area/article-type selection…

    1.2k GitHub stars~1.6k tokensUpdated 14 days ago
    Auto-check passed

Questions about Expecon Rebuttal

What does Expecon Rebuttal do?

A skill your agent uses when responding to a revise-and-resubmit or referee report for an Experimental Economics (ExpEcon) manuscript — including when a referee demands a new treatment, more…. Expecon Rebuttal is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when responding to a revise-and-resubmit or referee report for an Experimental Economics (ExpEcon) manuscript — including when a referee demands a new treatment, more sessions, or raises a deception/power concern.

When should I use Expecon Rebuttal?

Expecon Rebuttal fits situations like: responding to a revise-and-resubmit; referee report for an Experimental Economics (ExpEcon) manuscript — including when a referee demands a new treatment; raises a deception/power concern.

How do I install Expecon Rebuttal in Claude Code?

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

How do I install Expecon Rebuttal in Codex?

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

Can I use Expecon Rebuttal 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-rebuttal -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-rebuttal, .gemini/skills/expecon-rebuttal, .github/skills/expecon-rebuttal and .opencode/skills/expecon-rebuttal in your project.

What does Expecon Rebuttal need to run?

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

Does Expecon Rebuttal 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 Rebuttal 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 Rebuttal use?

Expecon Rebuttal 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 Rebuttal use?

About 2.1k tokens (SKILL.md is roughly 8.3k 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 Rebuttal?

Skills that share tags, products or a category with Expecon Rebuttal: Peer Review (spacering-net/codeg, 3.9k stars), Scholar Evaluation (spacering-net/codeg, 3.9k stars), Academic Paper Writing Pipeline (Imbad0202/academic-research-skills, 51k stars) and Academic Paper Reviewer (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Expecon Rebuttal?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 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.