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Run an evaluation against an eval with a specific config
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Basierend auf der SOC-Berufsklassifikation
Compare two eval runs and report what changed. Reads both runs' events, transcripts, and produced artifacts. Writes a short markdown summary classifying differences as regression, improvement, or neutral.
Generalized recursive iteration loop. Runs parallel sub-agents against a target, scores deterministically, diagnoses instruction gaps, applies fixes, and recurses until the stop condition is met or max depth is reached.
Write a handoff document so a new chat can continue the work
Show evaluation results and comparisons
Test-driven development of a Hono/Bun WebSocket application. Read requirements, read tests, build server, verify, iterate until all tests pass.
Scaffold a new evaluation
| name | run-eval |
| description | Run an evaluation against an eval with a specific config |
| argument-hint | <eval> [config] [--model MODEL] [--challenge NAME] [--prompt-variant VARIANT] [--keep] |
Run a Claude agent in a workspace, score the result, then compare against the most recent prior run.
Confirm with the user:
Do NOT launch until the user confirms.
$1 — eval name (directory in evals/)$2 — config name (directory in evals/<eval>/configs/, default: baseline)--model <name> — override model (default from EVAL.md frontmatter)--budget <usd> — override budget--challenge <name> — run only this challenge (matrix evals)--prompt-variant <name> — use prompt-<name>.md instead of prompt.md (e.g. --prompt-variant vague)--keep — keep workspace after completion for inspectionpython3 scripts/run_eval.py <eval> <config> [--model MODEL] [--budget USD] [--challenge NAME] [--prompt-variant VARIANT] [--keep]
run_eval.py handles everything: EVAL.md parsing, config resolution, challenge iteration, prompt templating, and invoke.py delegation. It always runs in stream mode so the agent's transcript is archived to stream.jsonl for /compare to read.
Use run_in_background: true for the run command. Monitor with python3 scripts/dashboard.py --latest.
python3 scripts/dashboard.py --latest --summary
/compare:/compare <prior-run-id> <current-run-id>
To find the prior run id: list evals/<eval>/results/ sorted by mtime, skip the current run, take the next one whose events.jsonl shows the same target and config in agent_started. If there is no prior run, skip the comparison and just show the run result.
The /compare skill spawns a sub-agent that reads both runs' evidence (events, transcript, produced artifacts) and writes a markdown summary. Print its output below the run summary so the developer sees both in one place.
If the developer ran multiple challenges (matrix eval), call /compare once per challenge — each comparison is independent.