From cognitive-psychology-skills
Structures response letters for Cognitive Psychology (Elsevier) major/minor revisions. Addresses each reviewer point, strengthens model-driven inference, and keeps the integrative argument coherent.
How this skill is triggered — by the user, by Claude, or both
Slash command
/cognitive-psychology-skills:cogpsych-rebuttalThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
A Cognitive Psychology **revision** typically asks for **more modeling rigor** — an additional
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.
cogpsych-writing-style).cogpsych-open-science-and-transparency).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).
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.
| Reviewer ask | Default home | Note |
|---|---|---|
| Fit a further rival model | Results + model-comparison table | refit all models under matched flexibility |
| Parameter / model recovery | appendix/supplement | summarize the result in one main-text sentence |
| Refit hierarchically / alternative priors | Results + diagnostics | report convergence; sensitivity in supplement |
| New experiment | Methods/Results (it is contribution) | integrate into the General Discussion synthesis |
| "Soften the theoretical claim" | General Discussion | scale wording to what the comparison licenses |
| Reproducibility / code | deposit + Open Practices statement | ensure fits regenerate in a fresh session |
【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
../../resources/official-source-map.md — review model, revision norms, reproducibility expectationsnpx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin cognitive-psychology-skillsDrafts point-by-point response documents and revision plans for Psychological Review decision letters. Classifies reviewer comments by theoretical demands and guides theory strengthening.
Structures a point-by-point response letter for a Psychological Science R&R, addressing reviewer requests for robustness, disclosure, and transparency while managing the journal's tight word budget.
Structures a response letter for a Psychological Bulletin revise-and-resubmit on a meta-analysis. Use when reviewer requests demand changes to the search, eligibility, model, or bias analyses.