Execution Assurance Bureau
AI generated repositories increasingly optimize for plausibility rather than behavioral correctness.
Core trick
Boots AI-generated repos, fuzzes endpoints, and flags README claims contradicted by observed runtime behavior.
Description
AI generated repositories increasingly optimize for plausibility rather than behavioral correctness. A repository can boot successfully, expose polished APIs, and still contain incomplete or non functional runtime behavior underneath.
RepoProbe is an execution assurance system for AI generated repositories. Instead of statically analyzing code, it executes repositories, probes runtime surfaces, fuzzes endpoints, verifies behavioral consistency, and compares observed runtime evidence against functionality claimed in repository READMEs.
The pipeline is intentionally split into two layers. Deterministic systems handle repository fingerprinting, execution planning, runtime probing, contradiction detection, and behavioral verification. Gemini 3.5 Flash is then used to synthesize runtime evidence and reason over contradictions without generating evidence itself.
The investigation system escalates suspicious runtime behavior into deeper probing workflows. For example, if an authentication endpoint returns invariant responses across malformed JWTs, empty credentials, and randomized payloads, RepoProbe flags the implementation as behaviorally inconsistent with its claimed authentication guarantees.
The terminal interface streams the investigation live as execution unfolds: runtime boot events, route discovery, contradiction escalation, fuzzing, trust score degradation, and final runtime assessment.
The project was built as infrastructure for a problem that is becoming increasingly common with AI generated software: code that looks production ready while remaining behaviorally incomplete under execution.
README excerpt
# repoprobe repoprobe is a cli-based managed execution assurance system for ai-generated software. it does not statically analyze repositories — it executes them, observes their runtime behavior, compares claimed functionality against observed reality, and then reports the truth. the project is being built for the google deepmind × cerebral valley hackathon at google i/o 2026. ## the problem software generation has become cheap, but verification has not. modern ai coding systems optimize for plausibility — convincing readmes, valid syntax, polished interfaces, and believable architecture. but plausibility is not correctness. a repository can compile successfully, boot successfully, render a polished frontend, and return http 200 responses while still being behaviorally false. authentication may always succeed regardless of input. payment systems may never actually contact stripe. database writes may silently never occur. claimed features may only exist in the readme. repoprobe exists because code authorship is now decoupled from code verification, and the industry lacks runtime-level tooling to bridge that gap. ## how it works a developer runs `repoprobe run ./target-repo` and the system takes over from there. repoprobe syncs the repository into a managed antigravity sandbox, uses gemini 3.5 flash to infer the minimum executable environment required for runtime observation, boots the application, discovers executable surfaces like routes and services and ports, probes ru