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Affordance examples previously carried a title plus a structured input object mirroring the inputSchema. Replace that with a description plus a command string holding a ready-to-run lark-cli invocation, which is what an AI agent driving the CLI actually consumes. No affordance data exists in the registry yet, so this only reshapes the consuming AffordanceCase type and its tests; the data pipeline (registry-config.yaml -> gen-registry.py -> meta_data.json) forwards the new keys verbatim.