arize-annotation

This skill focuses on annotation configs — the schema for human feedback — and on programmatically annotating project spans via the Python SDK. Human review in the Arize UI (including annotation queues, datasets, and experiments) still depends on these configs; there is no ax CLI for queues yet. Direction: Human labeling in Arize attaches values defined by configs to spans , dataset examples , experiment-related records , and queue items in the product UI. What is documented here: ax annotation-configs and bulk span updates with ArizeClient.spans.update_annotations . Proceed directly with the task — run the ax command you need. Do NOT check versions, env vars, or profiles upfront. If an ax command fails, troubleshoot based on the error: An annotation config defines the schema for a single type of human feedback label. Before anyone can annotate a span, dataset record, experiment output, or queue item, a config must exist for that label in the space.