Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add hanhuark/mechanical-engineering-research-skill --skill reviewer-author-loopgit clone --depth 1 https://github.com/hanhuark/mechanical-engineering-research-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hanhuark/mechanical-engineering-research-skill/reviewer-author-loop)<a href="https://agentmods.dev/skills/hanhuark/mechanical-engineering-research-skill/reviewer-author-loop"><img src="https://agentmods.dev/badge/skills/hanhuark/mechanical-engineering-research-skill/reviewer-author-loop/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hanhuark/mechanical-engineering-research-skill/reviewer-author-loop"><img src="https://agentmods.dev/badge/skills/hanhuark/mechanical-engineering-research-skill/reviewer-author-loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00094 | $0.01684 |
| Opus 5 | $0.00047 | $0.00842 |
| Sonnet 5 | $0.00019 | $0.00337 |
| Haiku 4.5 | $0.00009 | $0.00168 |
Grade A, and why
reviewer-author-loop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reviewer-Author Loop
Purpose
Use this skill to run a closed-loop manuscript improvement process:
- A Reviewer Agent evaluates the manuscript as a skeptical but constructive peer reviewer.
- An Author Agent revises the manuscript and response plan to address the review.
- A Verifier Agent checks that the revision actually resolves the comments and does not introduce new problems.
- 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
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 175 lines · 94 tokens per session scan A 3c5bd7f50631
reviewer-author-loop is a skill published in the GitHub repository hanhuark/mechanical-engineering-research-skill (16 stars, last pushed yesterday), licensed MIT. It adds 94 tokens to every session and 1,684 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-10.
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