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 EvoScientist/EvoSkills --skill paper-reviewgit clone --depth 1 https://github.com/EvoScientist/EvoSkillsWrote 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/evoscientist/evoskills/paper-review)<a href="https://agentmods.dev/skills/evoscientist/evoskills/paper-review"><img src="https://agentmods.dev/badge/skills/evoscientist/evoskills/paper-review/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/evoscientist/evoskills/paper-review"><img src="https://agentmods.dev/badge/skills/evoscientist/evoskills/paper-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00177 | $0.02363 |
| Opus 5 | $0.00088 | $0.01182 |
| Sonnet 5 | $0.00035 | $0.00473 |
| Haiku 4.5 | $0.00018 | $0.00236 |
Grade A, and why
paper-review 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 9d 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 — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Review
A systematic approach to self-reviewing academic papers before submission. Covers a 5-aspect review checklist, reverse-outlining for structural clarity, figure/table quality checks, and rebuttal preparation.
When to Use This Skill
- User wants to review or check a paper draft before submission
- User asks for feedback on paper quality or completeness
- User wants to prepare for potential reviewer criticism
- User mentions "review paper", "check my draft", "self-review"
If the user has already received reviewer comments and needs to write a rebuttal, use the
paper-rebuttalskill instead.
Prerequisites
Before starting review, confirm the paper-writing handoff checklist is satisfied: all sections drafted, claims anchored to evidence, limitation section present, figures finalized, and no unresolved \todo{} markers. If any item is incomplete, finish writing before reviewing.
The Perfectionist Approach
Strive for perfection: review your own paper, consider every question a reviewer might ask, and address them one by one.
The best defense against negative reviews is a thorough self-review:
- Adversarial review: Read your own paper as a critical reviewer would
- Seek advisor feedback: Ask your advisor to review — the more feedback, the better
- Address everything: For every potential weakness you find, either fix it or prepare a defense
Counterintuitive Review Protocol
Run this protocol before final polishing:
- Reject-first simulation: Force yourself to write a one-paragraph reject summary before writing any positive comments.
- Delete one unsupported strong claim: If a strong claim lacks direct evidence, remove it instead of defending it.
- Score trust, not only score gains: Papers with slightly lower gains but higher fairness and reproducibility often receive better review outcomes.
- Promote one explicit limitation: Move one meaningful limitation from hidden notes into the paper; transparency can increase confidence.
- Attack your novelty claim: Ask "Could a strong PhD derive this in one afternoon?" If yes, narrow and sharpen the novelty statement.
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.
- 9d ago First seen · 218 lines · 177 tokens per session scan A e86ffe859b37
paper-review is a skill published in the GitHub repository EvoScientist/EvoSkills (436 stars, last pushed 8d ago), licensed Apache-2.0. It adds 177 tokens to every session and 2,363 once invoked, about $0.0009 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.
Other skills, from other repositories
deltasci
Two-perspective co-reasoning for AI4Science hypothesis generation. Runs a structured 4-round dialogue between a domain scientist (parameterized by a domain pack) and an ML engineer, producing a grounded, falsifiable research hypothesis that is honest about the AI's training-distribution edges. Domain-agnostic via…
skill-creator
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
bio-ortholog-inference
Pull pre-computed ortholog calls from public databases (OrthoDB, Ensembl Compara, OMA browser, eggNOG, PANTHER, KEGG Orthology, HomoloGene) via their REST APIs. Use when orthologs are already curated upstream, when the question is "what is the X ortholog of Y" rather than "how to infer orthology de novo", when…
bioprobench
Score an LLM's biological-protocol reasoning on the BioProBench benchmark: protocol QA, step ordering, error detection, protocol generation, and LLM-judged error reasoning; or generate the responses.
arxiv-package
Package a TeX/LaTeX project into a clean tarball or zip for arXiv upload: file selection, build-artifact exclusion, 00README.XXX generation, ancillary file organization, archive validation. Triggers on: "package for arXiv", "create arXiv tarball", "bundle submission", "zip for arXiv", "prepare arXiv upload", "arXiv…
paper2poster
Convert academic papers (PDF) into conference posters (HTML/PNG). You are the conductor: you decide what each section needs — an original paper figure or text — write the outline, hand-author the poster HTML, and iterate on the render using your own visual read and a blind-reader content quiz. Use when the user wants…