Contact emails
[email protected]

Explainer
https://github.com/samuelgoto/agentic-login-toolkit


Specification
No information provided


Summary
A series of annotations that a website developer can introduce to their pages 
to help agentic browsers log users in.


Blink component
Blink>Identity>FedCM


Web Feature ID
fedcm


Motivation
In LLM-powered Agentic browsers, many user journeys involve logging in to 
websites. As with most of the LLM-powered actuation, the LLM has a baseline 
understanding using statistical models that allows it to click on links and 
fill forms to assist the user through the process. However, as much as user 
agents are and should develop as many heuristics as possible to retrofit into 
the existing content on the Web, heuristics are, by design, unreliable and are 
expected to have lower precision and quality than structured content that is 
opted-into by website owners. Not every website developer will have the 
incentives (expertise or demand) to annotate their content to be accessed by 
assistive browsers, but for those that do, what's the best way that they can 
annotate their page to make user agents (eg browsers and search engines) better 
aware of their login flows?


Initial public proposal
https://github.com/samuelgoto/agentic-login-toolkit


Requires code in //chrome?
False


Tracking bug
https://b.corp.google.com/issues/473826292


Estimated milestones

No milestones specified



Link to entry on the Chrome Platform Status
https://chromestatus.com/feature/5093444592730112?gate=5156788951449600


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