Peer review of research software

SkillAI & models

Covers community peer review of research software: preparing a package for JOSS, pyOpenSci or rOpenSci submission, self-checking against their review criteria before submitting, writing the paper or statement of need, responding to reviews, and acting as a reviewer or CODECHECK-style codechecker who executes the artifact. Use when the user mentions JOSS, pyOpenSci, rOpenSci or CODECHECK, wants to submit software for peer review or publication, asks whether their package is review-ready, or is reviewing someone else's research software for one of these venues. (PR-level code review is rseng-version-control-review; overall publication channel strategy is rseng-software-publishing.)

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What this skill tells your AI

The instructions your AI receives, as published by fdiblen/rseng-agent-skills in skills/rseng-software-peer-review/SKILL.md and read by ahel’s review.

Software peer review is the publication pathway where the SOFTWARE is the reviewed artifact: JOSS (any language), rOpenSci (R) and pyOpenSci (Python) run open, constructive reviews against public checklists, and CODECHECK issues certificates that a paper's computations were independently executed. For a maintainer, review readiness is a concrete bar to build toward; passing it earns a citable publication (JOSS papers get DOIs) and a community quality mark. This is review of the whole package - distinct from PR-level code review (rseng-version-control-review).

Pre-submission: self-review against the real checklist

Run the target venue's own checklist against the repository and fix failures BEFORE submitting - reviewers check exactly these:

  • License: OSI-approved LICENSE file at the root (rseng-licensing).
  • Documentation entry points: installation that works from a clean environment, usage examples that run, API docs for the public surface (rseng-documentation).
  • Statement of need: who this is for and what gap it fills - in the README and (for JOSS) the paper; write it for the target researcher, not the maintainer.
  • Tests that run in CI, covering the core claims of the software (rseng-testing, rseng-ci-cd); reviewers will run them.
  • Community files: contributing guidelines and code of conduct (rseng-community-governance).
  • Citation metadata and archiving: CITATION.cff, and a Zenodo (or equivalent) archive with DOI at acceptance (rseng-citation-metadata, rseng-publishing-releasing).
  • AI-usage disclosure: JOSS now asks about AI use in the submission - the project's aidecl.yaml (rseng-ai-declaration) is exactly the honest record to answer from.

Scope check before effort: each venue defines in-scope package types and substantiality; read the venue's scope page first and say honestly if the project is not there yet.

The JOSS paper: the user writes it

Short by design (750-1750 words): summary for non-specialists, statement of need, rough state of the field (neighboring tools and how this differs - rseng-discovery and rseng-software-reuse habits help here), acknowledgements, references with DOIs. It reviews the software; do not pad it into a methods paper. The agent's role is support only: outline against the venue's template, gather the material, check the draft against the criteria and verify its citations - never produce a submission-ready manuscript; authorship and every signed claim stay with the user (rseng-science-communication states the same boundary; JOSS itself asks about AI involvement - answer from aidecl.yaml).

Responding to reviews

Reviews are public issue threads. Respond to every point (fix, discuss, or explain why not), push commits as you go, and summarize changes when done. Tone: reviewers are volunteers improving your software - thank them, and disagree with reasons, not defensiveness.

Reviewing and codechecking

When the user is the reviewer:

  • Work through the venue checklist honestly - install from scratch in a clean environment (rseng-reproducible-environments), run the tests, run the examples; "it probably works" is not a review.
  • File findings as actionable issues, most important first; distinguish must-fix (checklist failures) from suggestions.
  • CODECHECK mode: execute the paper's workflow, record what reproduced (with outputs), what did not, and produce the certificate-style summary of exactly what was checked.
  • Constructive is the norm in this ecosystem: the goal is acceptance-after-improvement, not gatekeeping.

Working with this skill

This skill is source-independent: its authority is the venues' own review criteria and guides linked below.

Learn more (verified):

Related skills

Check whether any of these applies before moving on:

  • rseng-ai-declaration - JOSS asks about AI use
  • rseng-citation-metadata - CITATION.cff and DOI at acceptance
  • rseng-discovery - state-of-the-field section material
  • rseng-reproducible-environments - clean-room installs for reviewing
  • rseng-software-publishing - JOSS within the channel mix
  • rseng-version-control-review - PR-level review is distinct

Signals

GitHub stars
20
Forks
2
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
rseng-software-peer-review
Source
github.com/fdiblen/rseng-agent-skills