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Run an external evaluator loop for a BO run using a pre-provisioned backend id.
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Orchestrate an end-to-end chemistry or materials optimization study from a plain-English research question to BO execution and a paper draft.
BO execution layer — initializes a run from a resolved experiment spec, records observations, and continues through suggest/observe/report.
Initialize a BO run from a dataset or explicit search-space JSON.
Generate a final BO report and summarize optimization status.
Design and stabilize an expensive or fragile chemistry evaluator before BO setup.
Produce a lightweight chemistry or materials literature summary for research-agent, focused on baselines, key variables, and known constraints.
Basierend auf der SOC-Berufsklassifikation
| name | bo-run-evaluator |
| description | Run an external evaluator loop for a BO run using a pre-provisioned backend id. |
Use this skill when the user or operator has already provisioned an external evaluation backend and wants the BO loop automated.
This is a low-level execution helper. It does not build backends or reveal labeled datasets.
uv run python -m bo_workflow.cli run-evaluator \
--run-id <RUN_ID> \
--backend-id <BACKEND_ID> \
--iterations <T> \
[--batch-size <N>]
suggest / observe flow when observations are supposed to come from a human or lab system directlyThe resulting observations are recorded back into bo_runs/<run_id>/observations.jsonl with source benchmark-evaluator.