free_tool

Is your AI agent actually production-ready?

The model is rarely the problem; the loop around it is. Eight plain questions across the things that break agents in production: termination, escalation, tool-output integrity, idempotency, context, cost, and observability. Get a score, a per-dimension breakdown, and the two or three fixes worth doing first. About two minutes.

Question 1 / 80%

What stops your agent from looping forever?

Nothing explicit — we trust the model to decide when it's doneA generous max-iteration cap as a last-resort backstopA tuned iteration cap that fails closed when it's hitAn iteration cap plus loop detection for repeated/identical tool calls

how_scoring_works

How the score is built

Each answer carries weighted points, from "we trust the model to decide" up to a tested, guarded setup. We sum them and express your score as a percentage of the maximum, then map that to a band. Every dimension carries equal weight, so one strong area can't paper over a weak one.

It's a fast self-assessment, not an audit. It surfaces where the loop is most likely to break first, which is exactly where a real review would start.

0–44%At riskReal gaps between a demo and a dependable agent — runaway loops, injected instructions, side effects fired twice.

45–77%Getting thereThe core loop is sound; the risk now lives in the edges you haven't tested.

78–100%Production-readyDisciplined: it stops when it should, fails safely, and you can see and test what it does.

dimensions

What the assessment looks at:

Termination & loop caps
Escalation & failure handling
Tool-output integrity
Idempotency & side effects
Context management
Cost & rate control
Observability & evals

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Want your agent loop reviewed?

I'll go through what this scorecard surfaced and tell you where your loop breaks first. Book a call, or leave your email and I'll reach out.

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