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Review Writing

Community
doodledood
review-writing

Review any prose against its register's writing standard — a README, a spec, a design doc, a blog post, marketing copy, or a draft you paste in. Detects whether the text is documentation or human-voiced writing, applies that register's rules plus the rules holding in both, and reports graded findings with the fix. Use when checking a document's style, asking whether a draft reads as AI-written, reviewing writing before publishing, or asking for a writing review outside a manifest run.

Overview

Publisherdoodledood
Repositorymanifest-dev
Skill namereview-writing
Stars
77
Forks
10
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by doodledood on GitHub. Read the source before you install it.

Installation

Install the Review Writing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/doodledood/manifest-dev/tree/main/claude-plugins/manifest-dev/skills/review-writing
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/doodledood/manifest-dev.git /tmp/manifest-dev
mkdir -p .claude/skills
cp -r /tmp/manifest-dev/claude-plugins/manifest-dev/skills/review-writing .claude/skills/review-writing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Review Writing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Review Writing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Review Writing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

review-writing — review prose in its own register

Report where a text departs from the writing standard that governs it. Review only: you find and explain, the author decides and edits.

Input

$ARGUMENTS carries what to review — a file path, a directory, a glob, or pasted text. It may also name a register explicitly (register=docs, register=voice) to override detection. A manifest gate's body activates this skill with a register under the run's selected evaluator; the gate names the register and this skill owns the threshold.

With no argument, review the most recently modified prose file in the working tree and say which one you picked. If that is ambiguous or nothing prose-shaped has changed, ask what to review rather than guessing.

Registers and thresholds

Two registers, each with its own rules. The threshold is the bar a text must clear to PASS in that register:

RegisterWhat it coversRulesThreshold (PASS requires)
docsSpecs, proposals, reports, formal and technical documentation, READMEs, reference material, API docs../define/references/DOCS-STYLE-REFERENCE.mdno MEDIUM-or-higher findings
voiceArticles, blog posts, marketing and social copy, newsletters, narrative, creative writing../define/references/WRITING-REFERENCE.mdno MEDIUM-or-higher findings

Each register brings the shared floor with it: ../define/references/PROSE-FLOOR-REFERENCE.md holds the rules common to both, including the accessibility and inclusive-language floors, and a finding from the floor is graded and reported on the same footing as one from the register. There is no separate floor-only invocation.

The two thresholds sit at the same grade and still mean different things, because each register's severity anchor measures its own reader-facing cost — usability of documentation, or loss of meaning and intended voice in authored prose. Grade by the anchor of the register you applied, and never convert a finding from one scale to the other.

Load exactly two references: the floor, plus the one register's. Never load both register files for one text — their rules contradict each other by design, and a finding drawn from the wrong one is noise.

The paths above are where these files sit when the whole plugin is installed. Where they are absent — a single-skill install, or a host that lays skills out differently — search for them by name before giving up, and where they genuinely cannot be found, say so and report only the findings you can support without them rather than reviewing against remembered rules.

Detecting the register

Read enough of the text to judge what it is for. Documentation instructs or specifies: it tells a reader how something works or how to do something, and its value is in being followed. Human-voiced writing persuades, narrates, or entertains: it carries a perspective, and its value is in being read.

Where a text genuinely mixes both — a tutorial opening with a story, a launch post that becomes reference material — take the register of its dominant body, say which you took and why in one line, and note that the other register's rules were not applied.

Where detection is genuinely balanced, say so and ask, rather than picking silently. An explicit register= argument always wins and needs no explanation.

Precedence

A project's own style sheet or AUTHOR_VOICE.md, and any rule the user stated in the session or a context file, outrank the shipped references — in every register. Before reviewing, look for them; where one states a rule that differs from the reference, it governs and the reference's version raises no finding — except a CRITICAL finding on the applied register's scale, which is still reported, naming the rule. Say in the report which style source you applied.

Reporting

Report each finding with:

  • the severity and the rule area
  • the exact quoted prose, with its location
  • what the rule requires, and why this instance fails it
  • the concrete fix — the rewritten line where one line is enough, the shape of the change where it isn't

Order findings by severity, then by position in the text.

A clean text is a real result: say so plainly, name the register and reference set you applied, and stop. Never pad a report with marginal findings to look thorough — a manufactured finding costs the author more attention than it returns. When the text has many instances of one pattern, report the pattern once with two or three examples and a count, rather than one finding per instance.

Where a rule's application to this text is a judgment call, say that in the finding instead of grading it as a defect.

Scope, and what this is not

This skill reviews prose the user points it at, on request, in any register.

It does not overlap the prose-value dimension of review-code, which asks a different question on a different surface: whether prose inside a code change — code comments and repo doc files in a diff — earns its place at all. That dimension is diff-scoped and runs as part of a code review; this skill reads a whole text on demand and judges it against a style standard. Reviewing a README before publishing it is this skill; catching a comment that restates the line below it during a code review is that dimension.

If the user asks for the fixes to be applied after seeing the report, that is a separate request and ordinary editing.

Frequently asked questions

What does the Review Writing AI skill do?

Review any prose against its register's writing standard — a README, a spec, a design doc, a blog post, marketing copy, or a draft you paste in. Detects whether the text is documentation or human-voiced writing, applies that register's rules plus the rules holding in both, and reports graded findings with the fix. Use when checking a document's style, asking whether a draft reads as AI-written, reviewing writing before publishing, or asking for a writing review outside a manifest run.

Why use Review Writing on TypingMind?

Because you install it once and use it with any model. Review Writing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Review Writing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/doodledood/manifest-dev/tree/main/claude-plugins/manifest-dev/skills/review-writing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Review Writing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Review Writing?

As many as you like. As long as a model supports skills, you can use Review Writing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Review Writing AI skill free?

Yes. It is published on GitHub by doodledood under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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