prose-review

prose-review is a skill for Claude Code from w-winter/dot314. It costs 84 tokens per session (2,941 once invoked), scanned A, original, MIT.

A review skill for checking prose written for other people, including documentation, prompts, comments, and messages. It looks for unexplained jargon, missing context, unsupported references, and audience mismatch.

In plain words
What is it for?
Use it to review user-facing documentation, agent prompts, handoffs, task briefs, code comments, docstrings, emails, and similar prose.
Why use it?
It catches wording that makes text difficult for its intended reader to understand. It also helps ensure the writing fits the type of document being produced.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: mentions subagents.

Good fit Use it to review user-facing documentation, agent prompts, handoffs, task briefs, code comments, docstrings, emails, and similar prose.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/w-winter/dot314/prose-review
Install

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.

Any agent
npx skills add w-winter/dot314 --skill prose-review
Clone the repo
git clone --depth 1 https://github.com/w-winter/dot314

Made for: Claude Code.

Wrote 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.

agentmods badge for prose-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/w-winter/dot314/prose-review.svg)](https://agentmods.dev/skills/w-winter/dot314/prose-review)
Your own site
<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="Measured on agentmods" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,941 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00084 $0.02941
Opus 5 $0.00042 $0.01470
Sonnet 5 $0.00017 $0.00588
Haiku 4.5 $0.00008 $0.00294

Measured 3d ago against content hash 2767e0fb7504, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

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 3d 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.

skills/prose-review/SKILL.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 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 acid test for every artifact: could the intended reader use this text correctly for their purpose with only the text and any 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?

Read the full file on GitHub · 134 lines

Changes

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.

  1. 3d ago Changed · +34 tokens per session 2767e0fb7504
  2. 8d ago First seen · 134 lines · 50 tokens per session scan A 6153cbdd0f6d

Subscribe to this mod's changes

prose-review is a skill published in the GitHub repository w-winter/dot314 (130 stars, last pushed 2d ago), licensed MIT. It adds 84 tokens to every session and 2,941 once invoked, about $0.0004 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.