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Which AI tool needs a screenshot auto-loader next?

SlimSnap ships a Claude Code skill that auto-loads your latest screenshot so the agent reads the structured JSON without you pasting anything. That's the "magic" version of the workflow.

For everything else (Cursor, Lovable, bolt.new, Replit AI, claude.ai), the screenshot spec works but you paste the JSON into chat manually. It works, just not as smooth as the Claude Code flow.

Where do you actually paste screenshots into AI tools today? Vote in the comments, ideally with one line on what your screenshot loop looks like there. That tells me which agent gets the next auto-loader.

Don't take this as a date promise. Just trying to figure out which one to start with after the current backlog.

Six screenshot/AI requests from launch week. Which one should I ship next?

These came from people who tried the SlimSnap screenshot-to-JSON workflow during launch and asked for something specific. Listing in the order they came in.

  1. Screenshot capture for scrollable content and open dropdowns. Right now the capture clips to the visible window, so if a dropdown or long list is open, parts get cut. Balpreet S flagged this on LinkedIn.

  2. Native Mac app screenshot support (scope verification). Several people asked whether SlimSnap captures Linear / Notion / Figma desktop screenshots, or just browser windows. The answer changes who can use it.

  3. Confidence and overlap indicators on annotations. When the arrow is ambiguous (e.g. drawn between two close buttons in the screenshot), the JSON should signal that. Corey Clark asked on LinkedIn.

  4. Nested element hierarchy in the schema. Current screenshot schema is flat with bbox containment for nesting. Jyoti S Mohanty asked whether to make hierarchy explicit. Schema v2 candidate.

  5. Hybrid mode (JSON + raw screenshot). For users who want the safety net of pixels alongside the structured spec. Martin Zokov asked on X. Optional, would double the per-screenshot token cost.

  6. Windows screenshot support. Multiple people. OCR layer is Mac-native, so this is a real porting project, not a one-line change.

Which one should I build next? Vote in the comments, ideally with one line on why it matters for your screenshot workflow.

I have my own gut ranking but want to see what actual users prioritize.

SlimSnap - Your AI doesn't know which button you mean

The AI reads your screenshot as a pixel blob and guesses which button you meant. SlimSnap converts the screenshot plus your annotation into structured JSON: every element has coordinates, an ID, and your arrow points at a specific one. Around 700 tokens vs 1,568 raw on Sonnet. Free Mac app. Schema and Claude Code skill are open MIT. Runs entirely on-device.