Designing a reproducible multi-agent benchmark with AgentPlat

Choose the claim the experiment can actually test

A benchmark might ask whether a configured collective completes a workload under a stated fault profile. That is different from asking whether new developers understand the framework or whether every production deployment is reliable.

The evaluation methodology starts with a registered scenario and acceptance criteria. Write the target outcome and failure conditions before observing the run so the report cannot quietly redefine success afterward.

Freeze more than the source commit

The reproducibility checklist includes package lockfile, topology, population, roles, adapters, seeds, deterministic settings, fault schedule, budgets and host or database configuration.

For an illustrative recovery comparison, two executions at the same source commit can still differ if one uses a shorter lease or different fault timing. Record those inputs as part of the experiment rather than assuming the commit identifies the whole operating system.

Separate raw observations from derived scores

Keep registrations, shard artifacts and evaluator checkpoints apart from generated reports and interpretation. A later analysis can then explain exactly which evidence produced a score.

If the campaign is incomplete, retain that status. Do not drop a failed shard or rerun only difficult cases and present the combined output as one original execution. Follow-up experiments can be valuable when they have their own identities and conditions.

Make comparisons use an explicit baseline

A claim of improvement needs a defined comparison. Changing the model, topology and retry budget together may produce a useful exploratory result, but it does not isolate which change caused it.

The limitations guidance asks for observed conditions, unresolved cases and resource costs alongside results. Include these even when they make the headline less simple. Readers need them to decide whether the result applies to their own workload.

Publish an evidence package a reviewer can follow

1. State the registered question and acceptance criteria.
2. Identify the exact software, configuration and baseline.
3. Link the raw artifacts and checkpoint records.
4. Report attempted, completed and incomplete work.
5. Explain what the result supports and what remains unmeasured.

The adopter evidence guide separates implementation, distribution, usability and operational outcomes. Keep your benchmark in the appropriate evidence class instead of using it to answer unrelated adoption questions.