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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 18, 2026·2 points·0 comments

AI Analysis

●●SolidSolve My ProblemShip It

Vimium for Claude—drill into responses without touching the mouse, action-key shortcuts included.

Strengths
  • Solves a genuine daily friction point: text selection in long conversations is slow and error-prone
  • Hint-based drill-down (block → sentence → word) is faster than manual selection or copy-paste loops
  • Site-specific adapters for three major AI chatbots; adapts to light/dark themes without breaking
Weaknesses
  • Existing text-selection tools (browser find, copy extensions) partially solve this—not a wholly new category
  • Limited to chat interfaces; no integration with AI agent workspaces or notebooks
Category
Target Audience

Heavy AI chat users (Claude, ChatGPT, Gemini), especially researchers and developers

Similar To

Vimium · Vimium-C · Superhuman (for Gmail keyboard nav)

Post Description

I use Claude everyday (no joke) 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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