AgentProof shows the verification layer after agents write code.
I built AgentProof as a public harness for AI-built apps and pull requests: local commands, browser routes, screenshots, console errors, accessibility basics, broken links, launch-readiness score, machine JSON, and handoff notes.
What to inspect
Current target lanes
- AI Deployment Engineer for Codex: proof that real repos can be scoped, checked, and handed off safely.
- AI Systems Engineer, Codex Agents: traceability, tool-use failure surfaces, and verified task completion.
- Applied AI Engineer, Codex Core Agent: eval thinking around generated code, routes, reports, and user-facing proof.
- Developer Productivity / Quality & Developer Tools: CI action, local harness, score, report artifacts, and public docs.
Links
Local check
npm install
npm run build
npm test
node dist/src/cli.js audit . --no-browser
Boundary
Cleanroom Intelligence Works is the legally distinct proof-lab concept around this work. I act as founding CEO for that pre-incorporation build: ship small proof tools, reject fake scale, and keep claims tied to tests, reports, source links, and current role fit.
This page uses OpenAI and Codex only to name public target roles and source context. It is independent from OpenAI and does not use OpenAI logos, product UI, private systems, or affiliation language.
Sources checked: OpenAI Brand Guidelines, OpenAI engineering roles, and OpenAI Emerging Talent. The role-specific follow-up is the Codex deployment memo.