See what's wrong
with your agent.Fix the right things.
A full diagnostic for your AI agent across 32 dimensions of real capability, judged by a panel of independent frontier models from four labs. You get a ranked list of what to fix first.
What it does
for teams building custom agents and LLM applicationsAgent scorecards
Scores your agent on what actually matters — task accuracy, hallucination control, context handling and autonomy — rolled up from 32 proof-gated dimensions across four pillars.
Regression monitoring
Tracks performance over time, so you know immediately if a prompt change, a model update, or an edge case degrades the agent.
Proof-based scoring
Every score traces to evidence that actually ran — observed tool calls, signed transactions, real outputs. Claims and descriptions score zero.
Sovereignty — proof of real action
The paid tier scores what your agent can actually do in the world: sign a challenge, make a real micro-payment from a wallet it controls, hold a live endpoint, recall across sessions.
Where your agent actually sits
Every run places your agent across 12 behavioural classes and compares it to the median of its class. The shape tells you what kind of agent you have built — and which side of it is thin.
You build, fine-tune or manage AI agents. It saves hours of manual QA, keeps a prompt change from quietly breaking what worked, lowers API costs, and catches hallucinations before production does.
You are looking for a personal productivity tool. This is a developer and observability instrument, not a consumer assistant or chat app.
Run it once to find out what is actually wrong.
The first diagnostic is free, takes about 30 minutes, and publishes nothing unless you choose to.