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 archimedes-run/omniHarness --skill academic-paper-reviewgit clone --depth 1 https://github.com/archimedes-run/omniHarnessWrote 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/archimedes-run/omniharness/academic-paper-review)<a href="https://agentmods.dev/skills/archimedes-run/omniharness/academic-paper-review"><img src="https://agentmods.dev/badge/skills/archimedes-run/omniharness/academic-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/archimedes-run/omniharness/academic-paper-review"><img src="https://agentmods.dev/badge/skills/archimedes-run/omniharness/academic-paper-review.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 | $0.00095 | $0.02548 |
| Opus 5.5 | $0.00038 | $0.01019 |
| Sonnet 5.5 | $0.00019 | $0.00510 |
| Haiku 4.5 | $0.00010 | $0.00255 |
Grade A, and why
academic-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 1mo 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.
This is a copy
100% identical to academic-paper-review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Academic Paper Review Skill
Overview
This skill produces structured, peer-review-quality analyses of academic papers and research publications. It follows established academic review standards used by top-tier venues (NeurIPS, ICML, ACL, Nature, IEEE) to provide rigorous, constructive, and balanced assessments.
The review covers summary, strengths, weaknesses, methodology assessment, contribution evaluation, literature positioning, and actionable recommendations — all grounded in evidence from the paper itself.
Core Capabilities
- Parse and comprehend academic papers from uploaded PDFs or fetched URLs
- Generate structured reviews following top-venue review templates
- Assess methodology rigor (experimental design, statistical validity, reproducibility)
- Evaluate novelty and significance of contributions
- Position the work within the broader research landscape via targeted literature search
- Identify limitations, gaps, and potential improvements
- Produce both detailed review and concise executive summary formats
- Support papers in any scientific domain (CS, biology, physics, social sciences, etc.)
When to Use This Skill
Always load this skill when:
- User provides a paper URL (arXiv, DOI, conference proceedings, journal link)
- User uploads a PDF of a research paper or preprint
- User asks to "review", "analyze", "critique", "assess", or "summarize" a research paper
- User wants to understand the strengths and weaknesses of a study
- User requests a peer-review-style evaluation of academic work
- User asks for help preparing a review for a conference or journal submission
Review Methodology
Phase 1: Paper Comprehension
Thoroughly read and understand the paper before forming any judgments.
Step 1.1: Identify Paper Metadata
Extract and record:
| Field | Description |
|---|---|
| Title | Full paper title |
| Authors | Author list and affiliations |
| Venue / Status | Publication venue, preprint server, or submission status |
| Year | Publication or submission year |
| Domain | Research field and subfield |
| Paper Type | Empirical, theoretical, survey, position paper, systems paper, etc. |
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.
- 1mo ago First seen · 290 lines · 95 tokens per session scan A a0285baaeacc
academic-paper-review is a skill published in the GitHub repository archimedes-run/omniHarness (7 stars, last pushed today), licensed MIT. It adds 95 tokens to every session and 2,548 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to academic-paper-review, differing in 0 lines, and is treated as a copy.
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