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 TobiasBlask/open-paper-machine --skill peer-review-enginegit clone --depth 1 https://github.com/TobiasBlask/open-paper-machineWrote 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/tobiasblask/open-paper-machine/peer-review-engine)<a href="https://agentmods.dev/skills/tobiasblask/open-paper-machine/peer-review-engine"><img src="https://agentmods.dev/badge/skills/tobiasblask/open-paper-machine/peer-review-engine/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/tobiasblask/open-paper-machine/peer-review-engine"><img src="https://agentmods.dev/badge/skills/tobiasblask/open-paper-machine/peer-review-engine.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 | $0.00096 | $0.04438 |
| Opus 5 | $0.00048 | $0.02219 |
| Sonnet 5 | $0.00019 | $0.00888 |
| Haiku 4.5 | $0.00010 | $0.00444 |
Grade A, and why
peer-review-engine 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 10d ago.
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 — 507 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestration Log: When this skill is activated, append a log entry to
outputs/orchestration_log.md:### Skill Activation: Peer Review Engine **Timestamp:** [current date/time] **Actor:** AI Agent (peer-review-engine) **Input:** [paper source: draft.md / paper.tex, word count, number of sections] **Output:** 2 simulated reviewer reports saved to simulated_reviews.md **Recommendation distribution:** [R1: recommendation, R2: recommendation]
Peer Review Engine
Core Principle
The best time to discover weaknesses is before reviewers do. This engine generates two independent, simulated double-blind peer reviews that mimic the rigor, tone, and structure of top-tier IS/CS conference reviews (ICIS, ECIS, HICSS) and journal reviews (MISQ, ISR, EJIS, BISE). Each reviewer has a distinct persona and evaluation focus, producing complementary perspectives on the manuscript.
The reviews are actionable, not performative. Every weakness includes a concrete
suggestion for improvement. Every strength is specific enough to preserve during revision.
The output format is designed to feed directly into /respond-reviewers, creating a
pre-submission quality loop: write -> self-review -> revise -> submit.
When to Activate
- User says "review my paper", "simulate a peer review", "give me reviewer feedback"
- User says "review paper", "pre-submission check", "what would reviewers say?"
- After Phase 6 (LaTeX export) when the user wants quality assurance before sharing
- Before sending a draft to co-authors
- When the user wants to identify weaknesses before formal submission
- User runs
/review-paper
Prerequisites
draft.mdorlatex/paper.texexists (at least one)- Paper has identifiable sections (Introduction, Background, Method, Results/Findings, Discussion)
- If paper.tex exists and is more recent than draft.md, prefer paper.tex
Step 1: LOCATE & READ the Paper
Find the Manuscript
Check for paper sources in this order of preference:
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.
- 10d ago First seen · 507 lines · 96 tokens per session scan A fcab4bddd04c
peer-review-engine is a skill published in the GitHub repository TobiasBlask/open-paper-machine (18 stars, last pushed 5mo ago), licensed MIT. It adds 96 tokens to every session and 4,438 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 2026-08-30.
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