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agent-eval

Use when installing or using @primer/agent-eval, designing agent evaluations, creating benchmarks, experiments, scenarios, checks, judges, or treatments, and running, planning, sharding, or interpreting evaluations with the agent-eval CLI.

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primer/agent-eval
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October 8, 2026 at 22:14
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name
agent-eval
description
Use when installing or using @primer/agent-eval, designing agent evaluations, creating benchmarks, experiments, scenarios, checks, judges, or treatments, and running, planning, sharding, or interpreting evaluations with the agent-eval CLI.
# agent-eval Use agent-eval to measure how agents perform on real tasks and whether a change to their environment improves the result. ## Choose a task Read only the references needed for the current task. The overview is context, not a prerequisite for every operation. | Task | Read | | :------------------------------------------------------ | :--------------------------------------------------------------------------------- | | Install and complete a first evaluation | [Getting started](references/getting-started.md) | | Understand project structure and evaluation methodology | [Overview](references/overview.md) | | Establish a capability baseline | [Benchmarks](references/benchmarks.md), [capabilities](references/capabilities.md) | | Compare instructions, skills, agents, MCP, or plugins | [Experiments](references/experiments.md), [treatments](references/treatments.md) | | Create a task, starting workspace, or custom image | [Scenarios](references/scenarios.md) | | Add deterministic grading or a subjective rubric | [Checks](references/checks.md) or [judges](references/judges.md) | | Select models, effort, or execution backends | [Models and runners](references/models-and-runners.md) | | Install resources or run commands in a trial | [Sandbox](references/sandbox.md) | | Inspect a run matrix, shard, or merge | [Plans](references/plans.md) | | Read results or diagnose agent behavior | [Trials and results](references/trials-and-results.md) | | Find a command, flag, or runtime failure | [CLI](references/cli.md) | ## Execution rules - For a first comparison, use one scenario, one model/effort, and one treatment beyond the automatic control. - Keep prompts and fixtures treatment-blind. Put the knowledge being tested in treatment setup, not shared setup. - Withhold grader files using `files`. Verify the starter fails for the intended reasons and a correct solution passes; restore the starter before execution. - Inspect the plan's combinations before running. Use a fresh output directory. - Finish by reading trial results and reporting outcomes and errors separately. Command completion alone does not establish quality. - Interpret session AI credits using [Trials and results](references/trials-and-results.md); missing usage is not the same as zero cost. These references describe the source API at authoring time. For an installed version, verify its package types and `npx agent-eval <command> --help` before using an unfamiliar option. Do not substitute legacy CLI flags.
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