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 w-winter/dot314 --skill prose-reviewgit clone --depth 1 https://github.com/w-winter/dot314Wrote 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/w-winter/dot314/prose-review)<a href="https://agentmods.dev/skills/w-winter/dot314/prose-review"><img src="https://agentmods.dev/badge/skills/w-winter/dot314/prose-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/w-winter/dot314/prose-review"><img src="https://agentmods.dev/badge/skills/w-winter/dot314/prose-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 3 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- low Excessive Agency · line 104 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00084 | $0.02914 |
| Opus 5.5 | $0.00034 | $0.01166 |
| Sonnet 5.5 | $0.00017 | $0.00583 |
| Haiku 4.5 | $0.00008 | $0.00291 |
Grade A, and why
prose-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.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prose review
Review prose written to be read by someone else for language that doesn't belong in text its intended reader will encounter, and for missing grounding that a cold reader would need. Fix problems directly.
The main in-scope forms are:
-
User-facing documentation: READMEs, guides, reference docs, help text
-
Prompts for other LLMs: skills, system prompts, agent instructions, handoffs, task briefs
-
Inline comments: the
//and#prose a maintainer reads next to the code -
Docstrings: function, class, and module documentation, including generated API docs
-
Other-facing messages: issue or PR comments, status notes, release notes, messages, emails, and similar prose when the operator names them
The same failure modes run through all of them.
First: name the reader
Before reviewing each file or standalone artifact, state in one line who reads it, what they are trying to do, what they can and cannot see, and what genre it is (user README, contributor or architecture doc, operator runbook, agent prompt, handoff, task brief, inline comment, docstring, message, email, issue comment). Every judgment below is relative to that reader and purpose, not to a generic "new reader." Implementation detail is correct in a contributor-facing architecture doc or an inline comment and wrong in a user README; "what changed" is correct in a changelog and wrong in reference docs. Do not strip detail that this file's actual reader needs.
The intended reader must be able to use each artifact correctly with only its text and explicitly named, reachable dependencies, without access to the session, private plans, or other local material that informed the recent edits.
For prompts, handoffs, and task briefs: could a cold-start agent act correctly from this text and any explicitly named, reachable files, without access to the context window you currently have and without having to guess? For comments and docstrings: could a maintainer who can read the surrounding code, but who wasn't present when it was written, understand what this text is telling them?
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 Changed · +1 lines 901b49b43498
- 1mo ago Changed · +34 tokens per session 2767e0fb7504
- 1mo ago First seen · 134 lines · 50 tokens per session scan A 6153cbdd0f6d
prose-review is a skill published in the GitHub repository w-winter/dot314 (139 stars, last pushed today), licensed MIT. It adds 84 tokens to every session and 2,914 once invoked, about $0.0003 per session on Opus 5.5. 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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