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AsdPrompt – Vimium-style keyboard navigation for AI chat responses

AsdPrompt – Vimium-style keyboard navigation for AI chat responses

by contrary2belief·Feb 16, 2026·2 points·0 comments

AI Analysis

●●SolidSlickSolve My Problem

Vimium for Claude responses—select and drill-down entirely from keyboard, but narrow audience.

Strengths
  • Genuine pain point: eight mouse context-switches down to three keystrokes for common task
  • Drill-down UX (block→sentence→word) is clever; action keys ('elaborate', 'debug') inject prompts directly
  • Built in 2 days using Claude Code; technical insight on what became possible with AI coding
Weaknesses
  • Works only on three chat sites; would break if Claude/ChatGPT change DOM structure
  • Niche audience: must already live in terminal/keyboard-first world and use these specific chat UIs
Target Audience

Power users living in Claude/ChatGPT; researchers needing fast context switches; keyboard-first workflows

Similar To

Vimium · Tridactyl · GhostText

Post Description

I use Claude throughout the day and kept getting annoyed by the same thing: selecting text from responses with the mouse. Overshoot, re-select, copy, click input, paste. Especially bad in long conversations where you want to reference something from 30 turns ago.

asdPrompt is a Chrome extension that adds hint-based navigation (like Vimium) to AI chat interfaces. Cmd+Shift+S activates the overlay, hint labels appear next to every text block. Type a letter to select a block, then keep typing to drill down: block → sentence → word. Enter copies, or you can press an action key (e, d, x) to inject a follow-up prompt ("elaborate on [selection]") directly into the chat input.

Works on claude.ai, chatgpt.com, and gemini.google.com. Adapts to light/dark themes. Free. Built the initial MVP in 2 days using Claude Code — the adapter architecture, NLP segmentation pipeline, and Playwright test harness would have taken a month without it.

Tech details for the curious: site-specific DOM parsers behind an adapter interface, text segmentation via compromise.js with regex fallbacks for technical content (paths, camelCase break NLP libraries), bounding rectangles calculated via Range API + TreeWalker, overlay isolated in Shadow DOM. Tested with Playwright visual regression.

The landing page has an interactive tutorial where you can try the full drill-down mechanic without installing. Happy to talk about the implementation.

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