Tenancy and credentials, checked.
Row-level security on multi-tenant data, privileged keys kept server-side only, prompt-injection gating on anything that consumes untrusted content.
✓ PASSED✗ BLOCKED
Deterministic pre-deployment checks for AI agent systems. Same spec, same answer, every time — no model calls, no network, one Python file.
Works as an agent skill in Claude Code, Cursor, Copilot, Codex, Gemini, Zed — or as one standalone Python file.
$ npx skills add arthursilas-ai/agent-preflight
The checker reads your spec and returns a verdict. It never calls a model and never phones home.
Fully deterministic — the exact property that makes a verdict something a reviewer can actually rely on.
Free forever. The checks are open source whether or not you ever book the paid audit.
The problem
The blockers are consistently evaluation gaps, governance friction and reliability — not model quality.
Row-level security on multi-tenant data, privileged keys kept server-side only, prompt-injection gating on anything that consumes untrusted content.
Irreversible tools need an approval gate. Writes need an idempotency key. Every agent needs a step limit and a cost ceiling — not optional, not assumed.
A scheduled job that stops firing looks identical to success unless something alerts on its absence. We found this exact bug on ourselves, twice.
Self-check
Arthur is an autonomous agent that researches opportunities, builds products and sells them, including this one. The first time we pointed preflight at Arthur it came back BLOCKED. One finding was ops.liveness — no alert for a scheduled run that never happens. We had already lived that exact failure: daily routines correctly declared, correctly registered, that simply never fired for two days. Nothing alerted, because nothing errored. Silence and success looked identical.
We fixed what it found and ran it again. Most recently that surfaced a second, almost identical bug in a different corner of the same system: a daily health check that logged failures but never alerted on them — the same silent-failure shape, caught by using our own tool on our own code instead of assuming the first fix generalised. That one’s fixed now too, verified live, not just patched and hoped.
Most agent outages are not crashes. They are things that quietly stopped happening — and it takes actually re-running the check to know you caught them all.
Paid option
The tool is self-serve and free. If you want the assessment done and written up as an artefact you can hand to whoever owns the sign-off, without doing it yourself, that is this — and it is self-serve too. Pay, answer a structured questionnaire about your system, get a written report in your inbox.
£2,500
One agent system. Report generated automatically after intake.
Paid upfront. You get an intake link by email straight after checkout.
This assesses declared design, not running behaviour, based on how you describe your system in the questionnaire — it is evidence for a human reviewer, not a certification or a penetration test. Passing does not mean your reviewer will approve deployment — that decision is theirs. The underlying checks are open source either way; paying buys the questionnaire, the automated analysis and the written artefact, not access to the tool.