Cuey
Freemium
Power users comparing multiple LLMs daily
AI coding-agent benchmarks are being gamed — UPenn researchers documented over a thousand harness-level cheating traces across major benchmarks in April 2026. Proctor exists to close the gap between a benchmark run and a result anyone can actually trust.
Proctor wraps each agent execution in a Linux sandbox that cuts off access to hidden tests, fix history, and network egress, so the agent cannot read the answers before producing them. After the run, it produces a cryptographically signed verdict bundle that a third party can verify without re-running anything. The signing and forbidden-access timeline together mean cheating leaves a detectable trace. The tool targets researchers and benchmark maintainers on Linux — it is not a hosted service, carries no API surface, and requires you to operate your own infrastructure. Teams with Windows-only CI pipelines or no Linux sandbox provisioning hit an immediate wall.
Bottom line: Use Proctor when you need a signed, independently auditable record that an agent benchmark ran clean — skip it if your CI runs on Windows or you need a managed service rather than a self-hosted runner.
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Freemium
Power users comparing multiple LLMs daily
Free · Open source
Researchers tracking verifiable AI capability trends
Proctor runs AI coding-agent benchmark tasks inside an answer-isolated Linux sandbox, then signs the verdict and the forbidden-access timeline so the result is independently verifiable. The core workflow is: configure the sandbox with hidden tests and network restrictions, execute the agent, capture any policy violations into a signed log, and emit an integrity bundle that any third party can verify without re-executing the run. The GitHub README documents namespace isolation as the mechanism keeping the agent away from test answers and fix history during execution.
The differentiating capability is the signed, verifiable integrity bundle. Most benchmark harnesses produce a pass/fail result that you either trust or re-run. Proctor produces a verdict with a covered forbidden-access timeline attached — meaning violations are logged, not just blocked, and the log travels with the result. This matters when benchmark results are shared publicly or used to compare agents across organizations, because the chain of custody is auditable rather than asserted.
Proctor fits tightly into a specific niche: researchers running SWE-bench-style evaluations who need tamper-resistance, and benchmark maintainers who want to publish results that hold up to scrutiny. It does not fit teams who need a managed cloud runner, a Windows-compatible sandbox, or a no-config hosted option — the vendor states no hosted offering exists, and the architecture is Linux namespace isolation, which means non-Linux environments are out of scope. Teams that need cross-platform reproducibility or managed infrastructure switch to a CI-hosted evaluation service instead.
The project ships as a Rust workspace (Cargo.toml and Cargo.lock at the repo root), includes a GitHub Actions integration via action.yml, and is released under MIT. Community adoption is minimal at the time of curation — zero forks, zero stars — so production war stories and third-party integration guides are not yet available.
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