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Write

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tw93
write

Rewrites and polishes Chinese or English prose and product copy. Use when drafting, editing, localizing, or cutting AI tone. Not for code comments or commit messages.

Overview

Publishertw93
RepositoryWaza
Skill namewrite
Stars
7K
Forks
413
Bundled files
11
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.

  • 11 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by tw93 on GitHub. Read the source before you install it.

Installation

Install the Write 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.
  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/tw93/Waza.git /tmp/Waza
mkdir -p .claude/skills
cp -r /tmp/Waza/plugins/waza/skills/write .claude/skills/write
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Write 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 Write 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 Write 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.

Write: Cut the AI Taste

Prefix your first line with 🥷 inline, not as its own paragraph.

Strip AI patterns from prose and rewrite it to sound human. Do not improve vocabulary; remove the performance of improvement.

Outcome Contract

  • Outcome: the prose preserves the author's intent while sounding natural for its audience and surface.
  • Done when: meaning, factual claims, and structure are preserved unless the user asked to change them, and AI-like wording is removed; punctuation and CJK/Latin mixing pass the Punctuation Gate for the output language.
  • Evidence: supplied text, target audience, project style references, release or product state, and requested language.
  • Output: edited prose for pasted text; for repository edits, a scoped diff and the requested verification or delivery receipt.

Durable Context Preflight

See references/durable-context.md for when durable context is in scope and the redaction gate that applies before any of it becomes a durable rule.

For /write: the supplied text and current release state override memory. Durable preferences can set brevity, tone, and social-post shape; they do not override the hard rule to edit in place, keep meaning intact, and avoid change lists unless the user explicitly asks.

Core Stance

This skill is a catalog of smells, not a checklist to run top to bottom. Use it to recognize AI taste, then make judgment calls. The reference files are catalogs; do not try to apply every rule to every text. Applying more rules is not doing a better job.

  • Over-editing is failure, equal to under-editing. If a sentence is already natural, clear, and stable, leave it. Most polish is subtraction (cut repetition, summary-tone, restated conclusions), not phrase-by-phrase replacement.
  • A piece has a speaker. Smooth prose that could belong to anyone has lost something. Keep the author's colloquial words, cadence, knowledge and judgments; deliberate authorial or genre choices take precedence over these defaults. The author's affection, frustration, pride, gratitude and personal convictions are content, even when abstract or phrased as a conclusion. Preserve their intensity; do not require external evidence for a feeling or replace it with a neutral observation. Read nearby paragraphs and author revisions to separate a real stance from stock rhetoric. If that distinction is uncertain, keep the sentence. Do not invent emotion or turn "what I did" into "what you must do."
  • Banned-phrase lists and replacement tables are examples, not find-and-replace. A flagged word that reads naturally in context stays. Match the smell, not the string. When source material exists, check it before flagging the author's wording; restore their words rather than paraphrasing them. When restoring copy, trace that passage's diffs to the nearest version before the unwanted edit and compare the restored text exactly; do not choose an older, shorter version or rewrite unrelated paragraphs.
  • Prefer fewer, stronger edits. Three changes that matter beat thirty mechanical swaps that flatten the voice.

When distilling a new lesson into this skill, fold it into an existing principle instead of appending another banned phrase. This skill must not grow monotonically; collapsing specifics back into principles is part of maintaining it.

Pre-flight

  1. Locate the text. Read named files or discover posts in the supplied repository before asking the user to paste anything. For "latest N," freeze the dated article set and its language mirrors, then account for each as edited, unchanged with reason, or unavailable.
  2. Audience locked? If the intended audience is unclear and cannot be inferred from the text (blog reader vs RFC vs email), ask before editing. Junior engineer and senior architect prose should read completely different.
  3. Language detected from the text being edited, not the user's command:
    • Contains Chinese characters + release notes or social post mode loads references/write-zh-release-notes.md
    • Bilingual or translation review loads references/write-zh-bilingual.md and the language references for both versions
    • Product/site/app localization review across multiple locales loads references/write-product-localization.md; also load references/write-zh-bilingual.md when Chinese copy is present
    • Contains Chinese characters (default prose) loads references/write-zh.md
    • Otherwise loads references/write-en.md

Mode Picker

Default is a line-level rewrite of the supplied text. Take a mode only when its row matches, and load a mode file only when its row points at one.

AskMode
Release note, changelog entry, update-feed copyload references/mode-release-notes.md
Maintainer reply on a public issue or PRload references/mode-public-reply.md
Long draft with several sections, tables, or images that needs structural workload references/mode-long-form.md
EN/CN pair to check for driftBilingual Review
Product, site, or app copy across localesProduct Localization Review
Document, PDF, or white paper to reviewDocument Review
Paragraphs that read disconnectedParagraph Coherence
Tweet, thread, or launch postTweet / Social Post

Bilingual Review Mode

Activate when: mixed Chinese/English, "Chinese copywriting", "bilingual consistency", "release notes"

Load references/write-zh-bilingual.md; it owns the judgment half that the Punctuation Gate script does not check.

Product Localization Review Mode

Activate when: "本地化文案", "多语言文案", "localization copy", "i18n copy", product/site/app strings, release feed copy, runtime catalog, or a user asks whether localized copy feels native.

Load references/write-product-localization.md and follow its review procedure. If Chinese is one of the locales, also load references/write-zh-bilingual.md.

Document Review Mode

Activate when: PDF, document, white paper, "review this document", "check this document", "审稿"

Review checklist:

  • Privacy scan: Flag sensitive information whose disclosure is not authorized for the intended audience. Preserve identity and experience the author explicitly supplies for this document or has already published; job seeking, employer names, and locations alone are not grounds to stop or delete content. Resolve uncertain disclosure before exposing it.
  • Tone consistency: Flag voice shifts, register mismatches, formulaic phrasing.
  • Bilingual validation: For CN/EN pairs, confirm translation accuracy and terminology consistency. Apply Bilingual Review Mode rules.
  • Rendering check: Placeholder text remaining (Lorem ipsum, TODO, [TBD]), broken image links.
  • Durable-doc scan: If the document is a review report, scorecard, or diagnostic snapshot, flag dated claims, stale line references, private paths, repo-specific commands, and current-score framing. Recommend extracting stable rules instead of preserving the snapshot as evergreen guidance.

Output format: follow the requested review or rewrite; mention privacy only when an actionable disclosure concern remains.

Paragraph Coherence Mode

Activate when: "连贯性", "段落连贯", "可读性", "coherence", "flow check", "段落顺不顺"

For review requests, report issues; for explicit rewrite or file-edit requests, apply the minimal authorized fixes. Check each paragraph for:

  1. Flag transitions that abruptly shift topic without a signal.
  2. Flag paragraphs where the opening sentence does not follow from the previous paragraph's close.
  3. Flag rhythm issues: monotone sentence length (all short or all long across a whole paragraph).
  4. Suggest the minimal fix for each: one word, one reordered clause, one bridging sentence.

Output: for review, a numbered list with paragraph locations and minimal fix suggestions; for rewriting, the revised text or scoped file changes. Do not ask again to apply already-authorized edits.

Tweet / Social Post Mode

Activate when: "推特", "twitter", "X推文", "tweet", "social post", "折叠长度", "长文推特", "发文"

Load references/write-zh-release-notes.md for the five announcement rules (community lead, highlights over completeness, UX framing, one stance, native rhythm) and the casual invitation close. For English posts or projects without that community voice, keep the same structure in the project's own voice.

Hard Rules

  • Meaning first, style second. If removing an AI pattern would change the author's intended meaning, keep the original. Removing promotion does not remove legitimate product descriptions, licensing information, or related-product explanations. Broad copy cleanup does not authorize rewriting attributed quotations or testimonials; preserve their wording unless explicitly included in the edit scope, and distinguish any paraphrase from a verbatim quote.
  • No silent restructuring. Do not reorganize headings, reorder paragraphs, or merge sections unless structural changes are explicitly requested. Edit in place. Structural assets are not cleanup noise: image placeholders, links, frontmatter, and example blocks stay unless the user asked to remove them, and any deletion gets listed with its reason instead of discovered later in the diff. (Exception: references/mode-long-form.md treats structural cuts and merges as in-scope, since structure is the main problem there; it still proposes them as change-points first instead of doing them silently.)
  • No invented first-person experience. When ghostwriting as the author, every personal anecdote, tool history, opinion, and quote must come from the supplied material or the author's published writing, and so does any color used to replace a flagged phrase: fix by subtraction, not by fresh imagery. The material lacking an example is a question to ask, not a gap to fill. Before drafting in the author's voice (rather than editing supplied text), read one or two of their published pieces as the voice and length baseline.
  • Material gate before drafting long-form. When asked to write rather than edit, count what you actually hold before choosing a length: supplied experience, numbers, quotes, actions, and verifiable public sources. A category name is not a material, and a restated idea is not a second material. Reasoning connects material; it does not breed material. If you cannot name a distinct material for each planned section, the plan is longer than the evidence. Resolve it by researching first, asking at most three questions in one round, or shipping a shorter piece. A target word count is not a reason to pad with invented examples or a fourth phrasing of the same point.
  • Shorter than the first draft wants to be. Outward copy (README paragraphs, tweets, release notes, maintainer replies) defaults to the length of the user's previously accepted pieces; when a physical constraint exists (tweet fold line, single-line rendering), derive the budget from the constraint before writing, not after the user trims it.
  • Artifact-grounded claims. For launch copy, release notes, social posts, product pages, and public replies, ground factual claims in real source material: current app behavior, runnable artifact, screenshot, product page, release page, changelog, issue/PR, or user-provided draft. Do not present handoffs, plans, old memory, or stale screenshots as current product truth, and do not turn concrete product evidence into generic marketing language. Compare the draft against the shipping artifact and tighten until the two agree.
  • No em-dash. Never produce em-dash (U+2014) or en-dash (U+2013) in Chinese or English output. Em-dash is the strongest AI-tone fingerprint in this style of writing. Use commas, periods, colons, or parentheses to break clauses. Hyphen-minus (-) inside compound words is allowed; replace it with a space or a period when possible. When editing a draft that contains em-dashes, replace every one before returning the text.
  • Match the requested handoff. Pasted-text rewrites need no explanation. Repository edits need the scoped diff and verification; complete explicitly authorized commit/push steps under the project's rules. A prose-only output convention must not hide unfinished delivery.

Punctuation Gate

Before returning any produced text (a rewrite, or generated release / reply / social copy), resolve the checker across install layouts and run it:

bash
GATE=""
for candidate in \
  "<skill-base-dir>/scripts/check-punctuation.sh" \
  "<skill-base-dir>/skills/write/scripts/check-punctuation.sh"; do
  [ -f "$candidate" ] && GATE="$candidate" && break
done
[ -f "${GATE:-}" ] || { echo "punctuation gate not found under the installed skill base; reinstall Waza" >&2; exit 1; }
bash "$GATE" --lang <zh|en|ja|auto> <file>   # or pipe text via stdin

Replace <skill-base-dir> with the installed Write skill or Waza dispatcher directory. The first path covers direct/plugin installs; the second covers the inlined-root release ZIP.

It enforces character-level punctuation by locale (half/full-width marks, CJK/Latin spacing, em/en dashes) and skips code, inline code, URLs, and markdown link targets, so it never fires on code; the script header documents the exact rule set. Fix every finding while preserving meaning; --fix rewrites only the zero-ambiguity zh cases to stdout. --lang auto classifies the whole input by fixed priority: any kana routes to ja, else any CJK to zh, else any Hangul to ko (reserved, skipped), else en, so a mostly-Chinese text that merely quotes a Korean glyph still routes to zh; pass an explicit --lang for mixed-locale or predominantly-English text. The checker owns character-level punctuation only; quote direction and other judgment calls stay with you and the reference files.

Gotchas

What happenedRule
Used formal register for a blog draftMatch the target audience's register. Blog is conversational, not academic.
Applied Chinese/English spacing rules to a pure-English textBilingual spacing rules (半角/全角) only apply when the text mixes Chinese and English
User flagged one word as "not my voice"; only that instance was fixedA flagged word marks a smell class, not a typo. Sweep the whole text for the same class (same register, same template shape) before returning

Output

Follow the Outcome Contract. For batch edits, reconcile the original article set and mirrors before reporting completion. State missing source or verification without treating it as a pass.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Write AI skill do?

Rewrites and polishes Chinese or English prose and product copy. Use when drafting, editing, localizing, or cutting AI tone. Not for code comments or commit messages.

Why use Write on TypingMind?

Because you install it once and use it with any model. Write 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 Write in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tw93/Waza/tree/main/plugins/waza/skills/write. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Write?

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 Write?

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

Is the Write AI skill free?

Yes. It is published on GitHub by tw93 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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