How to Evaluate Agent Performance Across Different Scenarios

1. Evaluation dimensions

Task result – whether the intended outcome is actually achieved.

Output structure – whether the result is hand‑offable, auditable and can continue downstream.

Behavioral boundary – whether the agent makes unauthorized commitments, omits required human confirmation, or triggers risky actions.

Long‑term stability – whether examples that pass today still pass after rule or configuration changes.

These dimensions give different business scenarios a common language for judging correctness and evidence gaps.

2. Applying the framework to multiple scenarios

Scenario 1 – E‑commerce after‑sale replacement

Task result – determine if the case meets replacement or compensation criteria and whether human hand‑off is needed.

Output structure – include problem summary, draft reply, rule reference, manual‑confirmation flag, and hand‑off reason.

Behavioral boundary – prohibit direct promises such as “refund is already processed” or “replacement is arranged”.

Long‑term stability – replay old cases after policy updates to ensure outdated wording is not reused.

Scenario 2 – Manufacturing equipment maintenance

Task result – identify fault type, risk level, and proper handling priority before giving next steps.

Output structure – list missing information, recommended diagnostics, shutdown/upgrade conditions, and points requiring on‑site confirmation.

Behavioral boundary – do not issue strong commands when device model, alarm level, or operating condition is unconfirmed.

Long‑term stability – replay cases after new device models, manuals, or alarm rules are released.

Scenario 3 – Insurance claim pre‑review

Task result – verify material completeness, trigger conditions, and appropriate claim pathway.

Output structure – provide evidence list, relevant policy clauses, missing materials, audit suggestions, and nodes needing human review.

Behavioral boundary – never directly confirm payout, replace human approval, or relax exception interpretations.

Long‑term stability – re‑validate all samples when claim rules, exclusions, or limits change.

Scenario 4 – HR recruitment screening

Task result – decide if a candidate meets hard job requirements and merits the next interview round.

Output structure – output match summary, risk alerts, missing information, and recommended conclusion for recruiter review.

Behavioral boundary – do not treat age, school preference, or vague personality traits as hard elimination criteria.

Long‑term stability – replay old screening cases after job description, team hiring standards, or priority conditions are updated.

3. Turning dimensions into observable evidence

Without structured evidence teams can only say “something feels off”. Concrete artifacts let them pinpoint whether the failure lies in result, structure, boundary, or stability.

The value of evaluation is turning diverse errors into a unified, attributable, replayable and fixable set.

4. Minimal checklist to start evaluation

Write explicit task‑result definitions for each business scenario instead of vague statements like “handle inquiry”.

Define output structures that are naturally hand‑offable, auditable and flow‑ready.

Encode behavioral boundaries as hard rules, preventing the system from improvising based on tone or experience.

Prepare replay samples that cover rule updates, organizational changes and boundary cases for re‑validation.

When these steps are in place, evaluation moves from superficial results to systematic, scenario‑agnostic judgment of task completion, output usability, boundary compliance and long‑term stability.