# ProofStep

- **Event:** [Meta Global AI Developer Hackathon](https://cerebralvalley.ai/e/meta-ai-developer-hackathon)
- **When:** Oct 26, 12:00 PM – Nov 4, 9:00 PM (EST)
- **Where:** Online
- **Team:** [Sangwon Yoon](https://cerebralvalley.ai/u/Sangwon)
- **GitHub:** https://github.com/yoon-sang-won/proofstep
- **Demo video:** https://proofstep.vercel.app/demo
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2081

ProofStep is a stateful visual practice agent that coaches a five-step physical placement exercise on a printable 3x3 board. It distinguishes PASS, CORRECTION and UNCERTAIN, explains the rule evidence, and advances only after independent geometric checks succeed. A wrong placement stays at the same step for correction and reobservation; an occluded or unreadable image requests a retake. Later steps recheck all previously placed pieces, and progress survives a browser refresh.

Meta Muse Spark 1.3 observes image quality and board visibility. SAM 3.1 returns segmented object masks and boxes; the official Meta parser extracts mask centroids and extents. A deterministic homography and rule engine then check placement. The model cannot declare task completion. A separate local pixel scan verifies the empty board and registration, and does not claim a model was used.

Try the app: https://proofstep.vercel.app/?lang=en
The public demo clearly replays genuine hosted-Meta observations on synthetic inputs and recomputes the rules; it makes no new API calls. A separate bounded local live mode analyzes newly selected images with a private server-side key. The published dataset used 5 Muse + 11 SAM calls, and additional real browser correction/retry checks bring this task to 7 Muse + 13 SAM calls. Automated tests: 171 passed.

Scope is explicit: manual calibration, synthetic validation and box/cell overlays are implemented. Physical-camera accuracy, automatic marker detection, multi-frame recovery and the proposed larger evaluation study are not yet validated. This is an AI-assisted hackathon project built with Codex and DeepSeek during the event implementation period.

## More from Meta Global AI Developer Hackathon

- [RoboFactory AI](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2078)
- [After Eclipse](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2079)
- [Eswar Dev](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2080)
- [Pet-EyPlant](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2082)
- [Patria](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2083)
- [Jayant Dubey](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2084)

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Markdown version of https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2081. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt
