A skill your agent uses when writing the response to a Cognitive Psychology (Elsevier) major/minor revision.

MITAuto-check passedResearch & Science

Install Cogpsych Rebuttal

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

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cogpsych-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/Cognitive-Psychology-Skills/skills/cogpsych-rebuttal .claude/skills/cogpsych-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
cogpsych-rebuttal
GitHub stars
1.2k
Token cost
~1.6k tokens
SKILL.md length
565 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when writing the response to a Cognitive Psychology (Elsevier) major/minor revision.

  • Works in 6 steps: Read the editor's letter as the rubric.… → Point-by-point, every comment. Quote… → Strengthen the model inference, don't… → …
  • Writing the response to a Cognitive Psychology (Elsevier) major/minor revision
  • SKILL.md covers When to trigger, Strategy, Response-letter format and Worked micro-example…, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Cogpsych Rebuttal is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when writing the response to a Cognitive Psychology (Elsevier) major/minor revision. Reviews here often demand added experiments, more model comparisons, recovery analyses, or fuller reproducibility, so the response must address every point and strengthen the model-driven inference. Structures the response letter; it does not fabricate new results or model fits.

Its SKILL.md is about 1.6k 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 Reproducible research and 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

  • Writing the response to a Cognitive Psychology (Elsevier) major/minor revision
  • Tasks that involve Reproducible research
  • Tasks that involve Peer review

Example prompts

  • “/cogpsych-rebuttal”

Workflow steps

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

  1. Read the editor's letter as the rubric. Solve the decisive points first; the editor adjudicates
  2. Point-by-point, every comment. Quote each comment, then respond; never skip one.
  3. Strengthen the model inference, don't just defend. Many requests (fit a further rival, add
  4. Keep the program coherent. A new experiment or model should slot into the argument; update the
  5. Concede or rebut with evidence. Did what was asked (cite the location), or push back respectfully
  6. Keep the modeling reproducible. New analyses must be reflected in the deposited model/analysis

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

Cogpsych Rebuttal loads about 1.6k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 565 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

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). 565 words, ~1,556 tokens.

Download SKILL.mdSave it as .claude/skills/cogpsych-rebuttal/SKILL.md (or your agent's skills folder).
name
cogpsych-rebuttal
description
Use when writing the response to a Cognitive Psychology (Elsevier) major/minor revision. Reviews here often demand added experiments, more model comparisons, recovery analyses, or fuller reproducibility, so the response must address every point and strengthen the model-driven inference. Structures the response letter; it does not fabricate new results or model fits.

Revision Rebuttal (cogpsych-rebuttal)

A Cognitive Psychology revision typically asks for more modeling rigor — an additional experiment, a further model comparison, parameter/model recovery, alternative priors, or reproducible code — because the contribution is a model-driven theoretical claim. The response letter must convert every reviewer and reassure the editor that the model adjudication is now airtight, while keeping the integrative argument coherent.

When to trigger

  • A major/minor revision arrived and you are planning the revision + response letter
  • Reviewers requested added experiments, model comparisons, recovery, or open-code changes
  • A requested analysis or model would change the conclusion
  • Writing the cover note to the handling editor

Strategy

  1. Read the editor's letter as the rubric. Solve the decisive points first; the editor adjudicates among reviewers and decides the next round.
  2. Point-by-point, every comment. Quote each comment, then respond; never skip one.
  3. Strengthen the model inference, don't just defend. Many requests (fit a further rival, add recovery, cross-validate, refit hierarchically, share code) make the adjudication stronger — do them and say where. A request that exposes overfitting must be addressed, not waved away.
  4. Keep the program coherent. A new experiment or model should slot into the argument; update the General Discussion so the synthesis still holds (see cogpsych-writing-style).
  5. Concede or rebut with evidence. Did what was asked (cite the location), or push back respectfully with a reason (e.g., why a requested model is not identifiable) — don't add an analysis that quietly undercuts the claim without saying so.
  6. Keep the modeling reproducible. New analyses must be reflected in the deposited model/analysis code and regenerate in a fresh session (see cogpsych-open-science-and-transparency).

Response-letter format

For each reviewer comment:

> [Quoted reviewer comment]

Response: [What we did / why we respectfully disagree].
Change: [Manuscript section, supplement/appendix section, table/figure, or
         deposited-code file].

Open with a short summary of the main changes to the editor; group by reviewer; end each entry with the location (note when added analyses or experiments went to the supplement/appendix).

Worked micro-example (illustrative response entries)

For the recognition-memory program, a major revision asked for a further model and recovery.

> R2: You compare UVSD and DPSD, but a mixture model might fit better -
> have you ruled it out?

Response: We agree this rival should be tested. We added a finite-mixture
SDT model, fit under matched flexibility; it does not improve penalized fit
(dBIC = 9 favoring UVSD) and model recovery confirms the comparison is
diagnostic at our design's N/trials.
Change: Results (model comparison, Table 1 expanded); recovery → Appendix B;
         fitting code updated (deposit, fit_mixture.R).

> R1: Can you recover the DPSD parameters at your trial counts?

Response: Yes - we now report parameter recovery for all three models
(recovered values within credible intervals). This is why the model
comparison is interpretable rather than an artifact of identifiability.
Change: Appendix B (recovery); deposited code recovery_sim.R; one sentence
         in Results pointing to it.
Show full SKILL.md (242 more words)Show less

Revision triage — where each request lands

Reviewer askDefault homeNote
Fit a further rival modelResults + model-comparison tablerefit all models under matched flexibility
Parameter / model recoveryappendix/supplementsummarize the result in one main-text sentence
Refit hierarchically / alternative priorsResults + diagnosticsreport convergence; sensitivity in supplement
New experimentMethods/Results (it is contribution)integrate into the General Discussion synthesis
"Soften the theoretical claim"General Discussionscale wording to what the comparison licenses
Reproducibility / codedeposit + Open Practices statementensure fits regenerate in a fresh session

Recurring revision pushback and the venue fix

  • "You only ruled out one rival" → fit the additional model(s) under matched flexibility; report the penalized comparison and recovery; never argue from a single fit.
  • "Your better fit might be overfitting" → add cross-validation/penalized criteria and model recovery; if the edge does not survive, adjust the claim.
  • "I couldn't reproduce your fits" → ship seeded code + a pinned environment + a fresh-session run log; reference it in the response.
  • "The new analysis weakens the effect" → disclose it, interpret it, and scale the theoretical claim; concealment is the cardinal sin.

Anti-patterns

  • Ignoring or merging away a comment without a visible response
  • Defending a single fit instead of adding the requested comparison/recovery
  • Adding an experiment or model that breaks the program's coherence without re-synthesizing
  • Adding analyses that contradict the original claim without acknowledgment
  • Letting deposited model code/data drift out of sync with the revision

Output format

【Editor's decisive points】addressed first? [list]
【Coverage】every reviewer comment answered? [Y/N]
【Model inference strengthened】added comparison/recovery/hierarchy? [Y/N]
【Program coherent】new experiment/model integrated into the synthesis? [Y/N]
【Reproducible】deposited code updated + fits regenerate? [Y/N]
【Next】resubmit via Editorial Manager

Supplementary resources

© 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 Cognitive-Psychology-Skills/skills/cogpsych-rebuttal of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

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Questions about Cogpsych Rebuttal

What does Cogpsych Rebuttal do?

A skill your agent uses when writing the response to a Cognitive Psychology (Elsevier) major/minor revision. Cogpsych Rebuttal is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when writing the response to a Cognitive Psychology (Elsevier) major/minor revision.

When should I use Cogpsych Rebuttal?

Cogpsych Rebuttal fits situations like: writing the response to a Cognitive Psychology (Elsevier) major/minor revision; tasks that involve Reproducible research; tasks that involve Peer review.

How do I install Cogpsych Rebuttal in Claude Code?

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

How do I install Cogpsych Rebuttal in Codex?

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

Can I use Cogpsych 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 cogpsych-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/cogpsych-rebuttal, .gemini/skills/cogpsych-rebuttal, .github/skills/cogpsych-rebuttal and .opencode/skills/cogpsych-rebuttal in your project.

What does Cogpsych Rebuttal need to run?

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

Does Cogpsych 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 Cogpsych 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 Cogpsych Rebuttal use?

Cogpsych 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 Cogpsych Rebuttal use?

About 1.6k tokens (SKILL.md is roughly 6.2k 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 Cogpsych Rebuttal?

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Who maintains Cogpsych 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.