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Writing Assistance Apis

Community
webmaxru
writing-assistance-apis

Implements and debugs browser Summarizer, Writer, and Rewriter integrations in JavaScript or TypeScript web apps. Use when adding availability checks, model download UX, session creation, summarize or write or rewrite flows, streaming output, abort handling, or permissions-policy constraints for built-in writing assistance APIs. Don't use for generic prompt engineering, server-side LLM SDKs, or cloud AI services.

Overview

Publisherwebmaxru
Repositoryweb-ai-agent-skills
Skill namewriting-assistance-apis
Stars
53
Forks
5
Bundled files
6
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.

  • 6 bundled files

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

  • Open source

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

Installation

Install the Writing Assistance Apis 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/webmaxru/web-ai-agent-skills/tree/main/skills/writing-assistance-apis
  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/webmaxru/web-ai-agent-skills.git /tmp/web-ai-agent-skills
mkdir -p .claude/skills
cp -r /tmp/web-ai-agent-skills/skills/writing-assistance-apis .claude/skills/writing-assistance-apis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Writing Assistance Apis 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 Writing Assistance Apis 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 Writing Assistance Apis 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.

Writing Assistance APIs

Procedures

Step 1: Identify the browser integration surface

  1. Inspect the workspace for browser entry points, UI handlers, and any existing AI abstraction layer.
  2. Execute node scripts/find-writing-assistance-targets.mjs . to inventory likely frontend files and existing Summarizer, Writer, or Rewriter usage when a Node runtime is available.
  3. If a Node runtime is unavailable, inspect the nearest package.json, HTML entry point, and framework bootstrap files manually to identify the browser app boundary.
  4. If the workspace contains multiple frontend apps, prefer the app that contains the active route, component, or user-requested feature surface.
  5. If the inventory still leaves multiple plausible frontend targets, stop and ask which app should receive the Writing Assistance API integration.
  6. If the project is not a browser web app, stop and explain that this skill does not apply.

Step 2: Confirm API viability and choose the right surface

  1. Read references/writing-assistance-reference.md before writing code.
  2. Read references/examples.md when the feature needs a session shape for monitoring downloads, batch output, streaming output, or cancellation.
  3. Read references/compatibility.md when preview flags, browser channels, hardware requirements, or iframe constraints matter.
  4. Read references/troubleshooting.md when availability checks, creation, streaming, or session cleanup fail.
  5. Verify that the feature runs in a secure Window context and that the relevant permissions-policy feature allows access from the current frame.
  6. Choose the narrowest surface that matches the task:
    • Summarizer for article, document, or conversation summaries.
    • Writer for generating new text from a short prompt or writing task.
    • Rewriter for transforming existing text while preserving its intent.
  7. If the feature must run in a worker, on the server, or against a remote model provider, stop and explain the platform mismatch.
  8. If the project uses TypeScript, add or preserve typings that cover the specific browser APIs used by the feature.

Step 3: Implement a guarded session wrapper

  1. Read assets/writing-assistance-session.template.ts and adapt it to the framework, state model, and file layout in the workspace.
  2. Gate session creation behind the API's availability() method using the same create options that will be used at runtime.
  3. Treat availability() as a capability check, not a guarantee that creation will succeed without user interaction or download time.
  4. Create sessions only after user activation when creation may initiate a download.
  5. Use the monitor option during create() when the UI needs download progress.
  6. Use AbortController for cancelable create and run calls, and call destroy() when the session is no longer needed.
  7. Recreate the session instead of mutating options after creation; session options are fixed per instance.
  8. If the feature lives in a cross-origin iframe, require explicit delegation for each API that the frame needs.

Step 4: Wire UX and fallback behavior

  1. Surface distinct states for missing APIs, unavailable devices, downloadable or downloading models, ready sessions, in-flight generation, and aborted work.
  2. Keep a non-AI fallback for unsupported browsers, blocked frames, or devices that do not meet the current preview requirements.
  3. Strip or normalize HTML before summarization or rewriting when the source text comes from rendered page content.
  4. Use the batch methods when the feature needs the full result before continuing, and use the streaming methods when the UI should reveal output incrementally.
  5. Pass sharedContext only for persistent session-wide guidance, and pass per-call context only for request-specific background detail.
  6. Keep language options explicit when the feature depends on supported input, context, or output languages.
  7. Do not route generic chatbot, tool-calling, or open-ended assistant tasks through these APIs; switch to the Prompt API or another approved capability when the task is not summarization, writing, or rewriting.

Step 5: Validate behavior

  1. Execute node scripts/find-writing-assistance-targets.mjs . to confirm that the intended app boundary and API markers still resolve to the edited integration surface.
  2. Verify feature detection, secure-context checks, and availability() behavior before debugging deeper runtime failures.
  3. Test at least one batch call and one streaming call when the feature exposes both modes.
  4. Confirm that cancellation stops generation cleanly and that destroyed sessions are not reused.
  5. If the target environment depends on preview browser flags or channel-specific behavior, confirm the required browser state from references/compatibility.md before treating failures as application bugs.
  6. Run the workspace build, typecheck, or tests after editing.

Error Handling

  • If Summarizer, Writer, or Rewriter is missing, keep a non-AI fallback and confirm that the environment satisfies the browser and preview requirements before changing product logic.
  • If availability() returns downloadable or downloading, require user-driven session creation before promising that generation is ready.
  • If create() throws NotAllowedError, check permissions-policy constraints, missing user activation for downloads, browser policy restrictions, or user rejection.
  • If create() or a run call throws NotSupportedError, align the requested languages, output format, summary type, tone, or length with the browser's supported combinations.
  • If a call throws QuotaExceededError, shrink sharedContext, per-call context, or the user input before retrying.
  • If the feature must run in a worker or server context, stop and explain that the Writing Assistance APIs are window-only browser APIs.

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 Writing Assistance Apis AI skill do?

Implements and debugs browser Summarizer, Writer, and Rewriter integrations in JavaScript or TypeScript web apps. Use when adding availability checks, model download UX, session creation, summarize or write or rewrite flows, streaming output, abort handling, or permissions-policy constraints for built-in writing assistance APIs. Don't use for generic prompt engineering, server-side LLM SDKs, or cloud AI services.

Why use Writing Assistance Apis on TypingMind?

Because you install it once and use it with any model. Writing Assistance Apis 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 Writing Assistance Apis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/webmaxru/web-ai-agent-skills/tree/main/skills/writing-assistance-apis. 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 Writing Assistance Apis?

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 Writing Assistance Apis?

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

Is the Writing Assistance Apis AI skill free?

Yes. It is published on GitHub by webmaxru 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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