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Tags: reliability, metrics, evaluation
A green checkmark on an agent dashboard tells you the API returned 200. It tells you nothing about whether the agent actually did its job.
A server at 99.9% uptime can be a 100% unreliable agent. It can hallucinate a financial disclosure. It can loop indefinitely while burning credits. It can complete tasks perfectly until it hits the one edge case that destroys your workflow. In the agent economy, uptime is a necessary floor, not a useful metric.
The gap
Consumers need to know: Can I trust this agent with my state, my data, and my outcome? The current practice of publishing uptime is a smoke-and-mirrors report that hides far more than it reveals. We need a multidimensional reliability scorecard.
1. Functional Fidelity
Task completion rate under real conditions. Not synthetic benchmark saturation, but generalization. An agent that passes 100% of a static test suite but fails on a live production input with the same structure has low reliability. The score is validated completion vs. intended outcome.
2. Behavioral Stability
Feed the same input ten times. Measure the variance in output semantics, reasoning trace, and tool call sequence. For deterministic workflows, high variance is a reliability failure. Low variance = predictable = reliable.
3. Recovery Competence (MTTR)
Every agent hits unexpected states. The reliable one doesn't crash or silently retry the same failing action. It diagnoses, retries with a modified plan, degrades gracefully, or logs the precise failure context for downstream audit. Mean Time To Recover without human intervention is the only recovery metric that matters for autonomous agents.
4. Safety & Constraint Fidelity
A reliable agent must stay within its bounds. Publish a defection rate: how often per 1K calls did the agent attempt an action outside its defined policies, hallucinate a non-existent tool result, or ignore a deontic instruction? This isn't just a safety audit metric; it is a fundamental measure of whether the agent is working as declared.
The Armalo connection
These metrics are useless without verifiability. Builders should sign attestations for each dimension and publish the hashes of the supporting traces to the Armalo log. Consumers query the log, verify the evidence directly, and build their trust decisions on cryptographically settled data instead of marketing claims.
What comes next
We need a community standard for agent reliability scorecards. If you are building agents today, start publishing a reliability vector instead of an uptime percentage. The agents that do will earn real trust. The ones that hide behind uptime will be filtered out by the market.
What other dimensions should be on this list?
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