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.
The day I shipped this started with me yelling at Claude Code for the fifth time. I'd pasted a screenshot of a misaligned form. I'd typed "fix this." Claude moved the wrong input. I retyped. Claude moved a different wrong input. I gave up and fixed it manually.
The reason it kept guessing: it was reading raw pixels. It had no way to know which rectangle was the input I meant, so it picked one that looked plausible.
SlimSnap converts the screenshot into a spec the AI can parse element by element. Each element has coordinates, OCR text, color values, and (if you drew an arrow on it) a target reference saying "this one."
It also happens to be ~700 tokens versus the 1,568 raw screenshots cost on Sonnet (up to 4,784 on Opus 4.7+). That part is just bonus.
Open: the JSON schema (MIT, github.com/bickov/slimsnap-schema) and a Claude Code skill that auto-loads your latest capture (MIT, github.com/bickov/slimsnap-skill). The Mac app is closed but free.
Other tools (Cursor, Lovable, bolt.new, Replit, ChatGPT Vision): the spec works, but you paste the JSON into chat yourself. Cleaner than raw images. Not as smooth as the Claude Code auto-loader. Someone with time on their hands could write the equivalent skill for any of them.
A real question: which AI tool do you reach for most when you need to point at something specific on screen? Tells me where to build the next auto-loader.
About SlimSnap on Product Hunt
“Your AI doesn't know which button you mean”
SlimSnap launched on Product Hunt on June 11th, 2026 and earned 120 upvotes and 13 comments, placing #11 on the daily leaderboard. 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.
On the analytics side, SlimSnap competes within Design Tools, Productivity and Artificial Intelligence — topics that collectively have 1.4M followers on Product Hunt. The dashboard above tracks how SlimSnap performed against the three products that launched closest to it on the same day.
Who hunted SlimSnap?
SlimSnap was hunted by Alexander Bickov. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of SlimSnap including community comment highlights and product details, visit the product overview.
Alexander Bickov