I'm requesting an early TAG design review of the writing assistance APIs.

Proofreading is the process of examining a text carefully to find and correct errors such as grammar, spelling, and punctuation to generate an error-free text before it is published or shared. Browsers and operating systems are increasingly offering proofreading capability to help their users compose (examples: Oodles of improvements to Chrome's Spell Checking, Use Writing Tools with Apple Intelligence on Mac). Web applications can also benefit from such proofreading capability backed by language models for a variety of use cases.

We're proposing an API that uses language models to give web developers high-level functionalities for proofreading. Specifically:

1. Error Correction: Correct input text by the user
2. Error Labeling: For each correction made to each error in the input text, label the error type (e.g. spelling, punctuation, etc.)
3. Error Explanation: Annotates each error with a plain language explanation

Explainer

https://github.com/webmachinelearning/proofreader-api/blob/main/README.md

The explainer

• Includes the information requested by the Explainer Explainer.
• Follows the Web Platform Design Principles.
• Includes or links to answers to the Security/Privacy Questionnaire.
• Describes user research you did to validate the problem and/or design.

Where and by whom is the work is being done?

• GitHub repo: https://github.com/webmachinelearning/proofreader-api
• Primary contacts:
  • Queenie Zhang (@queeniezqq), Google, editor
• Organization/project driving the design: Google
• This work is being funded by: Google
• Incubation and standards groups that have discussed the design:
  • Web ML Community Group https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-03-12-cg-minutes.md#proofreader-api

Feedback so far

• Multi-stakeholder feedback:
  • Chromium comments: We are excited to start trialing this API with developers through origin trials and behind-a-flag experiments.
  • Mozilla comments:
  • WebKit comments:
  • Web developers:
    • Public feedback on https://github.com/webmachinelearning/proofreader-api/issues was mixed. To summarize, some themes we saw include: asking for more capabilities (e.g. integrating custom dictionaries; adding confidence score to correction output); desire to make sure the API performs efficiently in real-world use cases like proofreading during active editing of the text.

You should also know that...

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