Language Detector Api

This implements browser-native language detection using the experimental Language Detector API in client-side JavaScript or TypeScript apps. You get support checks, availability gating, model download flows, session management, and proper cleanup patterns for the new built-in capability. It covers permissions policy handling, confidence thresholding, and fallback strategies when the API isn't available. Worth noting this is a window-only browser API, so it won't help with server-side detection or cloud translation services. The procedures are thorough on lifecycle management and include specific guidance on iframe delegation and user activation requirements. Good if you're building progressive enhancement into a web app that needs client-side language detection without shipping a third-party model.

skills.sh installs: 151
GitHub stars: 31
last updated: Jun 3, 2026

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Install

$ npx -y skills add webmaxru/agent-skills --skill language-detector-api --agent claude-code

Installs into .claude/skills of the current project.

Files

Language Detector API

Procedures

Step 1: Identify the browser integration surface

Inspect the workspace for browser entry points, UI handlers, text-input flows, and any existing AI abstraction layer.
Execute node scripts/find-language-detector-targets.mjs . to inventory likely frontend files and existing Language Detector API markers when a Node runtime is available.
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.
If the workspace contains multiple frontend apps, prefer the app that contains the active route, component, or user-requested feature surface.
If the inventory still leaves multiple plausible frontend targets, stop and ask which app should receive the Language Detector API integration.
If the project is not a browser web app, stop and explain that this skill does not apply.

SKILL.md on GitHub