# falsify

- **Event:** [Built with Opus 4.7: a Claude Code hackathon](https://cerebralvalley.ai/e/built-with-4-7-hackathon)
- **When:** Apr 21 at 12:00 PM – Apr 27 at 2:00 AM (EDT)
- **Where:** Online
- **Team:** [Cuneyt Ozturk](https://cerebralvalley.ai/u/cuneytozturk)
- **GitHub:** https://github.com/sk8ordie84/falsify
- **Demo video:** https://youtu.be/vVZTNeak5PA
- **Gallery:** https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery/5

Teams ship AI accuracy claims that evaporate under scrutiny not from malice, but because the claim was never structured to be falsifiable. A "94% accuracy" number becomes 71% in production and nobody can tell whether the model drifted, the metric got relaxed, or the threshold moved after seeing the data.

Falsify is a CLI that forces pre registration: you cryptographically seal the metric, threshold, and dataset with SHA-256 before the experiment runs. Post hoc edits break the hash. CI exits 3. The audit trail writes itself.

Deterministic exit codes are the API — 0 pass / 10 fail / 3 tampered. CI gates on the code, humans read the trail. The claim either survives contact with the data, or it didn't happen.

Built entirely with Claude Opus 4.7: 5 skills, 2 subagents, 3 slash commands, 1 MCP server. 514 tests passing.

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Markdown version of https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery/5. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt