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Agent skill

Reviewer Author Loop

by hashgraph-online in hashgraph-online/awesome-codex-plugins

Iterative manuscript improvement workflow where a reviewer agent critiques, an author agent revises, a verifier checks the revision, and the loop repeats until acceptance or a human-pause condition…

Apache-2.0Auto-check passedResearch & Science

Install Reviewer Author Loop

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill reviewer-author-loop -a claude-code

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

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins reviewer-author-loop --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/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/hanhuark/mechanical-engineering-research-skill/skills/reviewer-author-loop .claude/skills/reviewer-author-loop && 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
reviewer-author-loop
GitHub stars
1.3k
Token cost
~2.1k tokens
SKILL.md length
950 words
Files
5 (incl. references)
Skills in repo
714
Repo updated
First seen
Licence
Apache-2.0

At a glance

Iterative manuscript improvement workflow where a reviewer agent critiques, an author agent revises, a verifier checks the revision, and the loop repeats until acceptance or a human-pause condition…

  • Works in 4 steps: Reviewer Agent → Author Agent → Verifier Agent → …
  • Virtual peer review
  • SKILL.md covers Purpose, Confidentiality, When To Use and Inputs To Identify, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Reviewer Author Loop is an agent skill from hashgraph-online/awesome-codex-plugins. Iterative manuscript improvement workflow where a reviewer agent critiques, an author agent revises, a verifier checks the revision, and the loop repeats until acceptance or a human-pause condition is reached. Use for virtual peer review, reviewer-author revision loops, rebuttal preparation, resubmission polishing, journal paper improvement, response-to-reviewers drafting, and deciding when additional data, experiments, theory, modeling, or author judgment is required before further revision.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `agents/openai.yaml`, `references/author-revision-protocol.md` and `references/pause-criteria.md`).

It sits in Research & Science, covering Peer review. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.

When your agent uses it

  • Virtual peer review
  • Reviewer-author revision loops
  • Rebuttal preparation
  • Resubmission polishing

Example prompts

  • “/reviewer-author-loop”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Reviewer Agent
  2. Author Agent
  3. Verifier Agent
  4. Re-Reviewer Agent

What it can do on your machine

Read from SKILL.md and the folder at commit 9e7b281. 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 (its code samples are mermaid).

    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

Reviewer Author Loop loads about 2.1k tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 130 tokens; SKILL.md has 950 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~130
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4k

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 hashgraph-online/awesome-codex-plugins at commit 9e7b281, republished under its Apache-2.0 licence (© hashgraph-online). 950 words, ~2,142 tokens.

Download SKILL.mdSave it as .claude/skills/reviewer-author-loop/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
reviewer-author-loop
description
Iterative manuscript improvement workflow where a reviewer agent critiques, an author agent revises, a verifier checks the revision, and the loop repeats until acceptance or a human-pause condition is reached. Use for virtual peer review, reviewer-author revision loops, rebuttal preparation, resubmission polishing, journal paper improvement, response-to-reviewers drafting, and deciding when additional data, experiments, theory, modeling, or author judgment is required before further revision.

Reviewer-Author Loop

Purpose

Use this skill to run a closed-loop manuscript improvement process:

  1. A Reviewer Agent evaluates the manuscript as a skeptical but constructive peer reviewer.
  2. An Author Agent revises the manuscript and response plan to address the review.
  3. A Verifier Agent checks that the revision actually resolves the comments and does not introduce new problems.
  4. The loop repeats until the reviewer recommends acceptance or the author/verifier reaches a pause condition requiring human input.

This skill is distinct from one-pass peer review. Its value is the revision loop, traceable comment resolution, and explicit stop/pause decision.

Confidentiality

If private manuscripts, reviewer reports, review archives, unpublished data, grant proposals, or confidential comments are provided, use them only for the current task. Do not copy private text into reusable skill files, public outputs, examples, or repositories. When extracting lessons from private materials, convert them into abstract process rules with no titles, author names, manuscript identifiers, wording, or identifiable facts.

When To Use

Use this skill when the user asks to:

  • simulate peer review and then revise the manuscript
  • alternate between reviewer and author roles
  • improve a paper until it is acceptable
  • prepare a response to reviewers or rebuttal
  • decide whether reviewer comments require new data, experiments, modeling, theory, or human judgment
  • re-review a revised manuscript after changes
  • audit whether author revisions truly addressed reviewer concerns

If the manuscript is in a specific technical field and a domain skill is available, use this skill as the process scaffold and the domain skill as the judgment layer.

Inputs To Identify

Before starting, identify what is available:

  • manuscript source: DOCX, PDF, LaTeX, Markdown, Overleaf folder, or plain text
  • target journal, conference, thesis committee, or funding program
  • current stage: pre-submission, revision, resubmission, internal review, final polish
  • existing reviewer comments or simulated review needed
  • editable source file and build/render method
  • user constraints: maximum loop count, acceptable aggressiveness, whether to edit files directly

Proceed with reasonable assumptions when the missing information is not blocking. Pause only when the missing information changes the revision path.

Loop Protocol

1. Reviewer Agent

Read the current manuscript and produce a decision-oriented review:

  • recommendation: accept, minor revision, major revision, reject, or human input required
  • core contribution and journal fit
  • major comments that affect validity, novelty, methods, interpretation, or evidence
  • minor comments that affect clarity, formatting, citations, or presentation
  • required evidence or analysis
  • acceptance criteria: what must change before the reviewer would recommend acceptance

Use references/reviewer-rubric.md for detailed review dimensions.

2. Author Agent

Convert reviewer comments into revisions:

  • map each reviewer concern to a concrete action
  • revise the manuscript, figures, tables, equations, references, and captions when possible
  • add caveats or limitations when a claim cannot be fully supported
  • avoid performative agreement: do not weaken or remove a claim if stronger evidence can support it
  • preserve a response log with comment, action, manuscript location, and residual risk

Use references/author-revision-protocol.md for revision strategy and response-log structure.

3. Verifier Agent

Check the revision before returning to review:

  • build/render the manuscript when possible
  • verify citations, references, figures, tables, equation numbering, and cross-references
  • check that every reviewer concern is addressed or explicitly marked unresolved
  • check that new text does not overclaim, contradict earlier sections, or introduce unsupported statements
  • check that figures/captions remain readable and aligned with the discussion

If editing files, do not claim completion until verification has been run or the inability to run it is reported.

Show full SKILL.md (388 more words)Show less
4. Re-Reviewer Agent

Re-review the revised manuscript against the previous acceptance criteria:

  • accepted or acceptable after editorial polish
  • minor revision remains
  • major revision remains
  • human input required

If more revisions are possible with available information, loop back to the Author Agent. If not, pause.

Stop And Pause Rules

Stop when the reviewer recommendation is:

  • accept
  • accept after minor editorial revision
  • ready for submission with only user-preference edits remaining

Pause and ask the user when progress requires:

  • new experiments, simulations, datasets, images, measurements, or raw files
  • an author decision on scope, claims, novelty, or target journal
  • domain knowledge not present in the manuscript or available sources
  • a new theory/model that cannot be responsibly invented from current evidence
  • confidential permissions or coauthor judgment
  • choosing among mutually exclusive revision strategies

Use references/pause-criteria.md to classify pause conditions and phrase the user request.

Output Format

During the loop, keep outputs concise and actionable:

  • Reviewer Decision
  • Required Revisions
  • Author Actions Taken
  • Verification
  • Remaining Risks
  • Next Loop Decision

When the loop stops, provide:

  • final recommendation
  • files changed
  • verification performed
  • unresolved risks or optional polish items

Coordination With Other Skills

In the manuscript workflow that motivated this skill, the reviewer-author loop acted as the process scaffold while other skills supplied specialist judgment or file operations.

When acting as the Reviewer Agent, use and cite companion skills as applicable:

  • academic-paper-reviewer: independent peer-review stance, editorial recommendation, major/minor comments, re-review after revision.
  • mechanical-engineering-research: domain-specific technical review for thermal-fluid physics, boiling/heat-transfer models, experimental design, uncertainty, equations, figures, and interpretation.
  • deep-research: targeted literature checks when a review comment depends on current or unfamiliar literature.

When acting as the Author Agent, use and cite companion skills as applicable:

  • academic-paper: manuscript restructuring, abstract/introduction/discussion revision, response-to-reviewer style writing, and paper-level coherence.
  • mechanical-engineering-research: technical rewriting, mechanistic framing, model explanation, analysis design, and engineering interpretation.
  • documents:documents: DOCX editing, rendering, visual QA, comments, and tracked document artifact work.
  • spreadsheets:Spreadsheets: spreadsheet inspection, data extraction, recalculation, and analysis tables.
  • zotero:Zotero: citation lookup, BibTeX export, reference cleanup, and citation-key insertion when Zotero or BibTeX is used.
  • presentations:Presentations: figure or slide-deck integration when manuscript figures are being adapted from presentation material.

For one-pass critique only, a peer-review skill is sufficient. Use this skill when the user wants iterative review, revision, verification, and re-review. In outputs, name the companion skills used for each loop stage so the workflow remains auditable.

Minimal Flow

mermaid
flowchart TD
    A["Manuscript + target journal"] --> B["Reviewer critiques"]
    B --> C["Decision + required revisions"]
    C --> D{"Can revise with available information?"}
    D -- "Yes" --> E["Author revises manuscript"]
    E --> F["Verifier checks build, citations, figures, claims"]
    F --> G["Reviewer re-reviews"]
    G --> H{"Acceptable?"}
    H -- "Yes" --> I["Stop: ready or near-ready"]
    H -- "No, revision possible" --> C
    D -- "No" --> J["Pause for human input"]
    J --> K["Human provides data, decisions, or theory"]
    K --> E

© hashgraph-online, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in plugins/hanhuark/mechanical-engineering-research-skill/skills/reviewer-author-loop of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • agents/openai.yaml
  • references/author-revision-protocol.md
  • references/pause-criteria.md
  • references/reviewer-rubric.md

Open the folder on GitHubat commit 9e7b281

Compare with similar skills

Reviewer Author Loop 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.

Reviewer Author Loop compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Reviewer Author Loop this skillhashgraph-online/awesome-codex-plugins1.3k—~2.1kAutomated safety check: PassApache-2.0
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

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Categories

Questions about Reviewer Author Loop

What does Reviewer Author Loop do?

Iterative manuscript improvement workflow where a reviewer agent critiques, an author agent revises, a verifier checks the revision, and the loop repeats until acceptance or a human-pause condition…. Reviewer Author Loop is an agent skill from hashgraph-online/awesome-codex-plugins. Iterative manuscript improvement workflow where a reviewer agent critiques, an author agent revises, a verifier checks the revision, and the loop repeats until acceptance or a human-pause condition is reached.

When should I use Reviewer Author Loop?

Reviewer Author Loop fits situations like: virtual peer review; reviewer-author revision loops; rebuttal preparation; resubmission polishing.

How do I install Reviewer Author Loop in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill reviewer-author-loop -a claude-code`. Or copy the skill folder (plugins/hanhuark/mechanical-engineering-research-skill/skills/reviewer-author-loop in hashgraph-online/awesome-codex-plugins) into .claude/skills/reviewer-author-loop in your project. Claude Code loads it when a task matches its description.

How do I install Reviewer Author Loop in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill reviewer-author-loop -a codex`. Or copy the skill folder (plugins/hanhuark/mechanical-engineering-research-skill/skills/reviewer-author-loop in hashgraph-online/awesome-codex-plugins) into .agents/skills/reviewer-author-loop in your project. Codex loads it when a task matches its description.

Can I use Reviewer Author Loop 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 hashgraph-online/awesome-codex-plugins --skill reviewer-author-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reviewer-author-loop, .gemini/skills/reviewer-author-loop, .github/skills/reviewer-author-loop and .opencode/skills/reviewer-author-loop in your project.

What does Reviewer Author Loop need to run?

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

Does Reviewer Author Loop 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 Reviewer Author Loop 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 Reviewer Author Loop use?

Reviewer Author Loop is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Reviewer Author Loop use?

About 2.1k tokens (SKILL.md is roughly 8.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.8k tokens, read only when the agent opens those files.

What are the alternatives to Reviewer Author Loop?

Skills that share tags, products or a category with Reviewer Author Loop: 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 Reviewer Author Loop?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,255 GitHub stars. The repository holds 714 skills in this directory. The repository was last updated on October 9, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.