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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.

Quellinformationen

Repository
primer/agent-eval
Letzte Quellaktivität
8. Oktober 2026 um 22:14
Erkannte Sprache von SKILL.md
Englisch
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Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

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SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
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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