What to do
Evaluate coding agents on reproducible repository tasks with hidden acceptance tests and a clean starting state. Score verified task completion, intervention, regressions, time, and cost—not the persuasiveness of the agent's explanation.
Design fair tasks
Each task should have a clear starting commit, issue description, allowed tools, and objective acceptance tests. Mix localized fixes with tasks that require repository discovery. Keep a holdout test so the agent cannot optimize only for visible assertions.
Capture the full run
Store the patch, command log, messages, elapsed time, token or credit use, test output, and human interventions. If the agent stops early or claims success incorrectly, record that as a failure mode rather than manually completing the run.
Score outcomes in layers
First require build and test validity. Then review correctness, maintainability, security, and scope discipline. Report repeated-run variance; agents can produce different outcomes from the same task.
- Verified completion rate
- Human interventions per run
- Regression and security findings
- Median time and cost
- Unnecessary file changes
Practical checklist
Continue researching
This guide is an editorial framework, not a product endorsement. Recheck vendor documentation and your organization's requirements before making a purchasing or security decision.