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 hamzabellouch/agent-skills --skill academic-nature-nature-reviewergit clone --depth 1 https://github.com/hamzabellouch/agent-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/hamzabellouch/agent-skills/academic-nature-nature-reviewer)<a href="https://agentmods.dev/skills/hamzabellouch/agent-skills/academic-nature-nature-reviewer"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/academic-nature-nature-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/hamzabellouch/agent-skills/academic-nature-nature-reviewer"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/academic-nature-nature-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 | $0.00184 | $0.01382 |
| Opus 5 | $0.00092 | $0.00691 |
| Sonnet 5 | $0.00037 | $0.00276 |
| Haiku 4.5 | $0.00018 | $0.00138 |
Grade A, and why
nature-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 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nature Reviewer Assessment Skill
Use this skill to simulate a Nature-style reviewer assessment package from the referee
side.
This skill is for reviewer-style manuscript evaluation, not for drafting the authors'
response. If the user wants rebuttal writing, route to nature-response.
Default stance
- Ground the review only in the local source basis plus manuscript facts supplied by the user.
- Evaluate the manuscript against source-grounded axes:
originality,scientific importance,interdisciplinary readership,technical soundness, andreadability for nonspecialists. - Return exactly
3 reviewer reports + 1 cross-review synthesisunless the user explicitly asks for another structure. - The three reviewers may differ only in
emphasis; do not invent reviewer identities, specialties, institutions, or biographies. - Identify who would be interested in the results and why.
- Identify technical failings that must be addressed before the authors' case is established.
- Distinguish clearly between what is supported, what is weak, and what is not assessable from the provided material.
- When the manuscript has a clear technical domain, use claim-dependent domain gates as supporting checks, but keep the output inside the same 3-reviewer
nature-reviewerstructure. - Do not claim the editor's final decision or certainty about fit to
Nature.
Accepted inputs
The skill may receive:
- full manuscript draft
- abstract, summary paragraph, or cover-summary style text
- introduction, results, discussion, or methods excerpts
- figure legends, selected figures, or result notes
- author notes in Chinese or English describing the claimed contribution
- pre-submission positioning notes
If the provided material is partial, perform a bounded review and mark the assessment boundary explicitly.
Workflow
- Identify the input scope and whether the job is a reviewer-style assessment rather than rebuttal drafting.
- Extract a shared manuscript fact base: main claim, visible evidence, claimed significance, likely readership, and visible limitations.
- Check readiness and label missing evidence or missing sections instead of inventing them.
- Assess the manuscript using the source-grounded axes.
- If the manuscript clearly falls into a technical domain covered by
references/domain-specific-review-gates.md, load only the relevant domain section and use it to sharpen the technical-soundness critique. - Generate
Reviewer 1,Reviewer 2, andReviewer 3using shared facts but different emphasis. - Generate a
Cross-review synthesisthat captures consensus and weighting differences. - Run QA for groundedness, coverage, role boundaries, and non-invention.
What ships with it
11 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.
- manifest.yaml 1.6 KB
- README_EN.md 2.1 KB
- README.md 1.8 KB
- references/domain-specific-review-gates.md 9.8 KB
- references/editorial criteria and processes.md 4.3 KB
- references/qa-checklist.md 1.8 KB
- references/report-structure.md 2.2 KB
- references/review-axes.md 3.2 KB
- references/reviewer-workflow.md 2.5 KB
- references/role-boundaries.md 2.5 KB
- references/source-basis.md 4.4 KB
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 · 130 lines · 184 tokens per session scan A 01621a7250b4
nature-reviewer is a skill published in the GitHub repository hamzabellouch/agent-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 184 tokens to every session and 1,382 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 2026-09-03.
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