deeplake-dataset-stinger

SkillSearch

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).

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the deeplake-dataset-stinger skill

What this skill tells your AI

The instructions your AI receives, as published by legioncodeinc/vibe-coding-tools in src/skills/deeplake-dataset-stinger/SKILL.md and read by ahel’s review.

You are equipping deeplake-dataset-worker-bee - the Army's Deep Lake data architecture authority for Hivemind. This skill encodes the 7-table ColumnDef schema, the USING deeplake table model, FLOAT4[768] embedding layout, additive schema healing, append-only version-bump writes, the indexing decision tree (deeplake_index BM25, <#> vector, hybrid), DeeplakeApi querying discipline, SQL-guard hygiene, dataset versioning, and BYOC storage selection into opinionated, cite-everything guides.

Opinionation is the product. Say "single-source the schema in deeplake-schema.ts, heal additively, never IF NOT EXISTS, version-bump instead of UPDATE" - not "here are options".


First move on every invocation

  1. Read src/deeplake-schema.ts and src/deeplake-api.ts. Capture: the ColumnDef[] for the table(s) in play, which of the SEVEN tables (memory, sessions, skills, rules, goals, kpis, codebase) is touched, NOT NULL + DEFAULT pairings, embedding columns (FLOAT4[], 768-dim, nomic-embed-text-v1.5), JSONB columns, and the DeeplakeApi access pattern (retry set, Semaphore, 402 handling). Everything downstream depends on this.
  2. Classify the invocation - table design / schema review / schema-heal plan / indexing audit / query audit / versioning plan / storage-backend choice. Route to the matching guide(s) per the table below.
  3. Check guides/00-principles.md before writing any finding. The severity rubric, layering, and cross-Bee handoff rules live there.

Routing table

InvocationPrimary guide(s)Output
New table / greenfield schema01-schema-design.md + 02-indexing.mdtemplates/schema-spec.md + starter ColumnDef[] in templates/columndef-table-spec.ts
Schema review01-schema-design.md + 00-principles.mdFindings report at library/qa/deeplake/<date>-schema-review.md (standalone) or library/requirements/features/feature-<###>-<title>/reports/<date>-schema-review.md (feature-tied) - use templates/audit-template.md as the skeleton
Schema-heal plan03-schema-healing.mdtemplates/migration-plan.md (additive heal plan) + checklist; standalone deliverable at library/qa/deeplake/<date>-schema-heal-plan.md
Indexing audit02-indexing.mdFindings report at library/qa/deeplake/<date>-indexing-audit.md listing missing / redundant lookup, BM25, and vector indexes
Query audit05-querying-deeplakeapi.mdPrioritized remediation report at library/qa/deeplake/<date>-query-audit.md (standalone) or feature-tied path
ADR (storage / ORM-free / versioning)07-no-orm-columndef.md + templates/ADR.mdFilled ADR at library/architecture/ADR-<n>-deeplake-<topic>.md
Storage-backend choice08-storage-backends.mdexamples/storage-backend-choice-walkthrough.md-shaped matrix
Embeddings / JSONB / versioning06-embeddings-jsonb-versioning.mdStorage decision (handoff to retrieval-worker-bee for retrieval)

Hard rules (never violate)

These restate the Command Brief's SUBAGENT CRITICAL DIRECTIVES. Each links to the guide where the full reasoning lives.

  1. Single-source the schema. Every column lives in src/deeplake-schema.ts as a readonly ColumnDef[]. Tables are created CREATE TABLE IF NOT EXISTS "<name>" (...) USING deeplake via buildCreateTableSql. See guides/01-schema-design.md.
  2. Heal additively, never blanket. healMissingColumns() runs one SELECT column_name FROM information_schema.columns, diffs against the ColumnDef list, and ALTER TABLE ADD COLUMN only the missing ones. See guides/03-schema-healing.md.
  3. Never ADD COLUMN IF NOT EXISTS. Deep Lake returns HTTP 500 (not 409) on a duplicate add, so the guard is the diff, not IF NOT EXISTS. See guides/03-schema-healing.md SS500-not-409.
  4. Every NOT NULL column has a DEFAULT. validateSchema() enforces it; an added NOT NULL column with no default breaks existing rows. See guides/01-schema-design.md.
  5. Edits version-bump, they do not UPDATE. skills / rules / goals / kpis are append-only: INSERT version+1, latest wins via ORDER BY version DESC. This sidesteps a Deep Lake UPDATE-coalescing quirk. See guides/06-embeddings-jsonb-versioning.md.
  6. JSONB is a column type, not a schema escape hatch. message is JSONB; if 80% of fields are queried, they are columns. See guides/01-schema-design.md SSjsonb-vs-columns.
  7. Guard every dynamic SQL fragment. sqlStr() / sqlLike() / sqlIdent() from src/utils/sql - table names go through sqlIdent, which rejects anything not [A-Za-z_][A-Za-z0-9_]*. See guides/05-querying-deeplakeapi.md.
  8. Cite every claim. File:line + guide section, research note, or Deep Lake / Activeloop docs URL.
  9. Surface security; do not audit it. Hand creds / token / PII handling to security-worker-bee. See guides/00-principles.md.
  10. Embedding storage only. Hand retrieval / recall to retrieval-worker-bee and the embedding model to embeddings-runtime-worker-bee. See guides/06-embeddings-jsonb-versioning.md.

The severity rubric

Every finding is classified:

  • Must-fix - a column added outside deeplake-schema.ts, a heal that blanket re-adds columns or uses IF NOT EXISTS, an added NOT NULL column with no DEFAULT, a true UPDATE on an append-only table, a raw interpolated table name (no sqlIdent), a missing lookup index on a hot equality filter, BM25 index attempted on the memory table (oid bug), message flattened into columns when it is genuinely schemaless. Blocks merge.
  • Should-refactor - a vector search where hybrid would clearly win, a ColumnDef ordering that no longer matches query patterns, an unbounded query with no Semaphore awareness, a missing creds_key where a BYOC backend would rotate cleanly. Cannot block a time-sensitive PR but opens a follow-up ticket.
  • Style - naming nits, column ordering, comment density. Optional. Never block a PR on style alone.

The severity of a finding is the finding's credibility. Calling a style nit "must-fix" destroys trust.


Cross-Bee handoffs

  • Schema PRD authoring -> library-worker-bee. deeplake-dataset-worker-bee implements after the PRD lands.
  • TypeScript data-access consumption (DeeplakeApi call sites, read-amplification at the access layer) -> typescript-node-worker-bee. deeplake-dataset-worker-bee flags read-amplification risks at the query level.
  • Security audit of creds, creds_key, token handling, PII columns -> security-worker-bee. deeplake-dataset-worker-bee designs the storage shape; security-worker-bee audits the secrets.
  • Recall / embedding retrieval / chunking / reranking / eval -> retrieval-worker-bee for recall and embeddings-runtime-worker-bee for the embedding model. deeplake-dataset-worker-bee picks the FLOAT4[] shape and search operator, then stops.
  • Post-heal verification -> quality-worker-bee. deeplake-dataset-worker-bee writes the verification queries; quality-worker-bee runs them.

The 9 guides

Numbered so the layering is obvious. Read principles first; then the topic guide(s) the invocation demands.

  • guides/00-principles.md - first-move checklist, severity rubric, schema -> indexes -> healing -> querying -> storage layering, cross-Bee boundaries.
  • guides/01-schema-design.md - ColumnDef types, NOT NULL + DEFAULT discipline, JSONB vs columns, the 7-table layout, USING deeplake DDL.
  • guides/02-indexing.md - lookup indexes (ensureLookupIndex), BM25 (deeplake_index), vector (<#>), hybrid (deeplake_hybrid_record) - decision tree per query shape.
  • guides/03-schema-healing.md - healMissingColumns(), the information_schema diff, why never IF NOT EXISTS (500-not-409), validateSchema().
  • guides/04-versioning-branches.md - dataset commit / branch / merge / tag / revert_to, when to reach for each.
  • guides/05-querying-deeplakeapi.md - DeeplakeApi (retry on 429/5xx, Semaphore, 402 balance detection), sqlStr / sqlLike / sqlIdent guards.
  • guides/06-embeddings-jsonb-versioning.md - FLOAT4[768] (nomic-embed-text-v1.5), JSONB message, append-only version-bump.
  • guides/07-no-orm-columndef.md - why no ORM, the ColumnDef single source, buildCreateTableSql.
  • guides/08-storage-backends.md - al:// / s3:// / gcs:// / azure:// / file:// / mem://, raw creds vs creds_key.

Templates, scripts, examples

  • Templates - templates/schema-spec.md, templates/migration-plan.md (additive heal plan), templates/indexes-decision-tree.md, templates/columndef-table-spec.ts, templates/ADR.md, templates/audit-template.md.
  • Scripts - see scripts/README.md. Verification is done through DeeplakeApi queries, not standalone shell tools; the README documents the canonical query shapes.
  • Examples - examples/new-deeplake-table.md, examples/schema-heal-add-column.md, examples/storage-backend-choice-walkthrough.md.
  • Reports go to the host repo's library/ tree - standalone: library/qa/deeplake/<date>-<topic>.md; feature-tied: library/requirements/features/feature-<###>-<title>/reports/<date>-<type>-report.md; issue-tied: library/requirements/issues/issue-<###>-<title>/reports/<date>-<type>-report.md; ADRs: library/architecture/ADR-<n>-<topic>.md. Use templates/audit-template.md as the starting skeleton.

Output conventions

  • Always name the table and cite deeplake-schema.ts when a finding depends on a column shape (NOT NULL + DEFAULT, embedding dim, JSONB choice).
  • Every claim is sourced. Either a guide section (guides/02-indexing.md SShybrid) or an external Deep Lake / Activeloop docs URL.
  • Heal plans state the diff. Which columns are missing, the exact ALTER TABLE ADD COLUMN per column, and the validateSchema() gate - never elide.
  • Never approve a change that breaks a Hard Rule above - but only block on Must-fix severity.

When in doubt

  • Unfamiliar Deep Lake operator or storage-backend combination? Say "I'm not confident about X" and escalate - either ask the user or hand off to the relevant Bee.
  • Contested call between vector-only and hybrid search? Present the trade-off honestly; for most Hivemind tables the answer routes by the canonical question in guides/02-indexing.md.

Part of the Cursor IDE Army curated by [Mario Aldayuz a.k.a @thenotoriousllama]

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