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 whoisraibolt/paper-skills --skill paper-reviewergit clone --depth 1 https://github.com/whoisraibolt/paper-skillsWrote 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/whoisraibolt/paper-skills/paper-reviewer)<a href="https://agentmods.dev/skills/whoisraibolt/paper-skills/paper-reviewer"><img src="https://agentmods.dev/badge/skills/whoisraibolt/paper-skills/paper-reviewer/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/whoisraibolt/paper-skills/paper-reviewer"><img src="https://agentmods.dev/badge/skills/whoisraibolt/paper-skills/paper-reviewer.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 | $0.00105 | $0.02957 |
| Opus 5 | $0.00053 | $0.01478 |
| Sonnet 5 | $0.00021 | $0.00591 |
| Haiku 4.5 | $0.00011 | $0.00296 |
Grade A, and why
paper-reviewer 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 12d 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 — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
paper-reviewer — deep pre-submission review
A reimplementation of the Paper Assistant Tool (PAT) architecture (Jayaram et al., Google Research, arXiv:2606.28277) on Claude Code subagents in place of Gemini Deep Think.
The premise from PAT, which is what makes this skill worth more than "read the paper and criticize it": a single reading pass spends its reasoning budget uniformly and shallowly. Segmenting the manuscript, giving each reviewer the whole text as context but only one segment to verify, then consolidating with deduplication and grounding checks, raises real-error detection substantially. On the Math/CS subset of the SPOT benchmark, this orchestration took the same model from 55.2% to 89.7% detection.
It produces no score, no ranking and no accept/reject recommendation. It produces objective errors and actionable improvements.
Writing counterpart: paper-writer. Writing and reviewing are separate passes by
design; whoever writes does not approve their own text in the same context.
Stage 0 — Resolve the target
- If the user named a file, use it. Otherwise look for the most likely
manuscript in the current directory (a
.texwith\documentclass, or a long.md) and confirm with the user before spending agents if there is more than one candidate. - Accepted formats are
.tex,.md,.pdfand.docx, and source beats the rest. PAT lists PDF parsing failure among its three most reported limitations, and a.docxcosts a conversion the source does not. If a.texor.mdexists, use it and ignore the compiled PDF. - Read the whole manuscript before segmenting. Without that, the segmentation comes out wrong.
- Locate verification inputs, if they exist:
- the
.bibor reference file; - data, result tables or experiment outputs in the repository (for example
data/outputs/), which allow checking number by number; - previous reviews, audits or referee reports (for example
reviews/,response_*.md,HANDOFF.md), which serve to avoid repeating a point already resolved.
- the
What ships with it
3 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.
- 12d ago First seen · 278 lines · 105 tokens per session scan A 3512621aac07
paper-reviewer is a skill published in the GitHub repository whoisraibolt/paper-skills (1 stars, last pushed 16d ago), licensed MIT. It adds 105 tokens to every session and 2,957 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 2026-08-31.
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