视觉画布设计
canvas-design
基于设计原则创作静态视觉作品,用于海报与品牌图形。
document-modeling【文档与办公】Model multimodal data with DocArray BaseDoc schemas, predefined documents, DocList, DocVec, nested fields, and typed tensors.
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Use this sub-skill when a task needs to define, validate, or batch multimodal DocArray data models.
BaseDoc schemas for text, image, audio, video, embeddings, metadata, and nested multimodal payloads.TextDoc and ImageDoc versus custom BaseDoc subclasses.create_doc() or create_doc_from_dict().DocList versus DocVec for streaming, reranking, shuffling, or contiguous ML batch processing.DocList fields, optional fields, and shape-checked NdArray tensor fields.serialization-storage.vector-indexing.DocList, DocVec, NumPy, or optional tensor backends fail.Run schema_smoke.py in an environment where DocArray is installed to confirm the main schema, dynamic document, DocList, typed tensor, and optional DocVec paths:
Run these commands from this sub-skill root (the directory containing this SKILL.md):
python scripts/schema_smoke.py --help
python scripts/schema_smoke.py
python scripts/schema_smoke.py --skip-docvec
The verified minimum scope is CPU with DocArray base plus proto, pandas, and web extras. Optional services and tensor frameworks are documented as boundaries, not verified defaults.