deeplake-dataset-stinger

deeplake-dataset-stinger is a Databases & SQL skill for AI agents, published by legioncodeinc in the that-git-life repository on GitHub. Skillspace rates deeplake-dataset-stinger B (83/100) and it passed the safety scan; the rating is based on static analysis only.

Designs, reviews, and heals the Hivemind Deep Lake data layer - the 7-table ColumnDef schema, USING deeplake DDL, FLOAT4[] embeddings, additive schema healing, append-only version-bump writes, deeplake_index / vector / hybrid search, DeeplakeApi querying, SQL guards, dataset versioning, and BYOC storage. Use when the user says "design this table", "review this ColumnDef", "is this index right?", "should this be a JSONB column or a tensor?", "we need a new NOT NULL column on the memory table", "how do we heal a missing column?", "vector or hybrid search here?", "which storage backend?", or when `deeplake-dataset-worker-bee` is invoked. Do NOT use for PRD authoring (library-worker-bee), TypeScript data-access consumption (typescript-node-worker-bee), security audits of creds / PII / token handling (security-worker-bee), or recall / embedding retrieval pipelines (retrieval-worker-bee for recall, embeddings-runtime-worker-bee for the embedding model).

Grade

B

Quality

83 / 100

Safety

Passed

GitHub stars

72

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