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Design the evaluation before running the agent. A good protocol makes one decision easier; a large collection of unplanned metrics usually does not.

1. Name the decision

Examples:
  • Should we enable resumable event consumption for this workflow?
  • Does the new retry policy reduce unresolved tasks without unacceptable cost?
  • Can the integration meet a p95 latency target in our staging topology?
  • Does the provider effect match the approved action in every trial?
Write the action you will take for pass, fail, and inconclusive results.

2. Define the evidence class

3. Build a task matrix

Sample across the real risk dimensions instead of selecting only happy paths: Keep private customer data out of the benchmark. Use synthetic or consented, redacted fixtures with documented provenance.

4. Freeze the treatment

Record before execution:
  • source revision and dependency lock;
  • model, provider, reasoning settings, and prompts;
  • tool registry and capability policy;
  • environment image and deployment topology;
  • token, step, elapsed-time, and concurrency budgets;
  • task order, randomization, warmup, and cache policy;
  • grader version and success rubric;
  • exclusions, retries, and stop rules.

5. Choose metrics

Use a small hierarchy:
  1. Safety vetoes — cross-tenant disclosure, unapproved effect, secret leak, false success, or failed cleanup.
  2. Primary outcome — task success or independently verified effect.
  3. Reliability outcomes — unresolved rate, parse errors, exact replay, reconciliation success.
  4. Resource outcomes — latency, tokens, steps, requests, and cost.
  5. Diagnostic outcomes — failure class, tool choice, retry count, and event reconnects.
Do not average away a safety veto.

6. Define evidence records

Use opaque identifiers and redacted digests. Keep secret inputs in the secure evaluation system, not the public artifact.

7. Run a pilot, then freeze the confirmatory protocol

Use the pilot to find broken fixtures, ambiguous grading, missing telemetry, and unrealistic budgets. Do not repeatedly tune on the confirmatory task set. After the pilot:
  1. correct the protocol;
  2. freeze the task set or sampling procedure;
  3. freeze analysis code and thresholds;
  4. run the confirmatory study once;
  5. publish missing and excluded trials;
  6. retain raw redacted records for review.

8. Report all outcomes

Publish:
  • counts before rates;
  • per-task outcomes and aggregates;
  • unresolved and invalid trials;
  • safety vetoes;
  • resource use;
  • confidence or uncertainty appropriate to the design;
  • deviations from the protocol;
  • limitations and unsupported claims.

Acceptance template

Metrics glossary

Define each outcome and denominator before collecting it.

Reproduction workflow

Package the protocol, environment, raw records, analysis, and claim boundary so another team can inspect the result.
Last modified on August 14, 2026