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 Zaoqu-Liu/ScienceClaw --skill manuscript-review-revisegit clone --depth 1 https://github.com/Zaoqu-Liu/ScienceClawWrote 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/zaoqu-liu/scienceclaw/manuscript-review-revise)<a href="https://agentmods.dev/skills/zaoqu-liu/scienceclaw/manuscript-review-revise"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/manuscript-review-revise/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/zaoqu-liu/scienceclaw/manuscript-review-revise"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/manuscript-review-revise.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 | $0.00118 | $0.02140 |
| Opus 5 | $0.00059 | $0.01070 |
| Sonnet 5 | $0.00024 | $0.00428 |
| Haiku 4.5 | $0.00012 | $0.00214 |
Grade A, and why
manuscript-review-revise 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 8d 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 — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Manuscript Review & Revision System
Evaluate and improve scientific manuscripts through a closed-loop process: Score → Identify Weaknesses → Revise → Re-score → Compare. Inspired by APRES (Meta Superintelligence Labs, ICLR 2026).
Core Principles
- Never modify core scientific claims — preserve all data, results, and conclusions
- Never add unverified data or fabricated citations — only restructure existing content
- Every revision has a stated reason — traceable, auditable changes
- Quantitative before/after comparison — ScholarEval scores pre and post revision
- Improve presentation, not science — clarity, structure, flow, completeness
When to Use
- User says
/reviewor/review <path-to-manuscript> - User asks "帮我审一下这篇论文" or "review my manuscript"
- User asks "润色" or "polish this draft"
- After ScienceClaw generates a research report, offer: "需要用审修系统优化这份报告吗？"
Workflow
Phase 1: ScholarEval Assessment (8 Dimensions)
Score the manuscript on each dimension (0.00–1.00):
| Dimension | Weight | Evaluation Criteria |
|---|---|---|
| Novelty | 15% | Does this advance knowledge? Are claims clearly differentiated from prior work? |
| Rigor | 25% | Methodology sound? Statistics correct? Controls adequate? Sample sizes reported? |
| Clarity | 10% | Writing clear? Figures self-explanatory? Logical flow between sections? |
| Reproducibility | 15% | Methods detailed enough to replicate? Software versions stated? Data accessible? |
| Impact | 20% | Does this matter for the field? Broad or narrow implications? |
| Coherence | 10% | Do all parts fit together? Introduction → Methods → Results → Discussion aligned? |
| Limitations | 3% | Are limitations honestly acknowledged? Not buried or trivialized? |
| Ethics | 2% | Ethical standards met? IRB mentioned if applicable? Conflicts disclosed? |
Compute weighted average. Output initial verdict: accept (≥0.75), minor_revision (≥0.60), major_revision (≥0.40), reject (<0.40).
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.
- 8d ago First seen · 176 lines · 118 tokens per session scan A 528733ce040b
manuscript-review-revise is a skill published in the GitHub repository Zaoqu-Liu/ScienceClaw (60 stars, last pushed 5mo ago), licensed MIT. It adds 118 tokens to every session and 2,140 once invoked, about $0.0006 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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