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 Mathews-Tom/armory --skill manuscript-reviewgit clone --depth 1 https://github.com/Mathews-Tom/armoryWrote 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/mathews-tom/armory/manuscript-review)<a href="https://agentmods.dev/skills/mathews-tom/armory/manuscript-review"><img src="https://agentmods.dev/badge/skills/mathews-tom/armory/manuscript-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/mathews-tom/armory/manuscript-review"><img src="https://agentmods.dev/badge/skills/mathews-tom/armory/manuscript-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00070 | $0.04508 |
| Opus 5 | $0.00035 | $0.02254 |
| Sonnet 5 | $0.00014 | $0.00902 |
| Haiku 4.5 | $0.00007 | $0.00451 |
Grade A, and why
manuscript-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 10d 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 — 441 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Manuscript Review Skill
Pipeline position: Phase 1a (content audit). Runs in parallel with figure-rhetoric. No prior dependencies. Outputs consumed by manuscript-provenance (macro manifest feedback) and figure-rhetoric (claims map for visual argument assessment). See companion skills for full pre-publication coverage: manuscript-typography (typographic conventions), citation-audit (citation truth), arxiv-preflight (submission compliance).
Purpose
Execute a comprehensive, multi-pass diagnostic audit of an academic or technical manuscript, producing a structured improvement report that identifies issues across 24 audit dimensions — from macro-coherence and argumentative architecture through claims-evidence calibration, narrative flow, prose microstructure, rendered visual inspection, and cross-element coherence, down to citation hygiene and reproducibility.
The output is a prioritized, actionable improvement plan — not a line edit. The goal is to surface structural, logical, and clarity issues that authors systematically miss because they're too close to the text.
Optimized for arXiv/preprint submissions with flexible compliance standards.
Companion skill: manuscript-provenance audits whether manuscript content
(numbers, tables, figures, ordering, terminology) is computationally derived
from code and scripts. This skill audits the document as prose; that skill
audits computational grounding. Run both for complete pre-publication coverage.
Boundary Agreement with manuscript-provenance
| Concern | This skill (manuscript-review) | manuscript-provenance |
|---|---|---|
| Reproducibility | Does the paper describe enough to reproduce? (§6) | Does the code actually produce what the paper claims? (§1, §7) |
| Figures/Tables | Legible, accessible, well-formatted? (§12) | Generated by scripts, not manual entry? (§2, §3) |
| Rendered visuals | Readable at print scale? Floats near references? (§23) | Figure generation script produces correct format? (§3) |
| Hyperparameters | Listed in the paper with rationale? (§6) | Values trace to config files, not hardcoded? (§1, §8) |
| Code availability | Statement exists in the paper? (§17) | Repo URL valid, README accurate, pipeline works? (§11) |
| Terminology | Abbreviations consistent within document? (§14) | Terms match code identifiers? (§5) |
| Significant figures | Consistent precision within document? (§12) | Precision matches script output? (§2) |
| Figure format | Appropriate format for document quality? (§12) | Format generated by script, not manually exported? (§3) |
| Computational cost | Reported in the paper? (§7) | Values trace to benchmarking scripts? (§1) |
| Macro-prose coherence | Prose framing appropriate for injected value? (§24) | Value traced to code, macro manifest produced? (§4) |
| Cross-element consistency | Prose, captions, figures, tables mutually consistent? (§24) | All elements from same run/pipeline output? (§9) |
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.
- 10d ago First seen · 441 lines · 70 tokens per session scan A c87d22042425
manuscript-review is a skill published in the GitHub repository Mathews-Tom/armory (316 stars, last pushed 4d ago), licensed MIT. It adds 70 tokens to every session and 4,508 once invoked, about $0.0003 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.
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