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databricks-lakebase

Databricks Lakebase Postgres: projects, scaling, connectivity, Lakebase synced tables, and Data API. Use when asked about Lakebase databases, OLTP storage, or connecting apps to Postgres on Databricks.

Quality

89%

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SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An exceptionally actionable, well-structured body: executable commands with full JSON payloads, explicit validation checkpoints around destructive operations, and detailed offload of depth to six well-described reference files. The only weaknesses are mild redundancy (drop-schema workflow repeated in two places) and one reference file (medallion-from-cdc.md) that is orphaned from SKILL.md's navigation.

DimensionReasoningScore

Conciseness

The body is dense with non-obvious product specifics (500-role limit, NULLIF RLS pattern, pooled-connection '' vs NULL, Data API open defaults) with no basic-concept padding, and the legacy Provisioned material is framed as retired context. Minor trimmable redundancy: the drop-schema recovery workflow appears in both the Schema Permissions section and the Troubleshooting table row, and version-specific details sit outside a deprecated section. Not 5 due to these repeated/could-be-tightened spots; well above 3 since nearly every token carries product knowledge Claude cannot infer.

4 / 5

Actionability

Fully executable throughout: complete CLI commands with --json payloads (create/update/delete project, branches, endpoints), a copy-paste scriptable block extracting HOST/TOKEN via python3, a JSON-path table for connection values, concrete SQL grant sequences, and an exact apps create-update JSON body. Covers the common cases (create, verify, connect, attach to app, grant, troubleshoot). Minor placeholder (<USERNAME>) does not detract from copy-paste readiness.

5 / 5

Workflow Clarity

Multi-step flows are explicitly sequenced with validation: create-project is followed by verify commands (list-branches/endpoints/databases) and an endpoint-size check; the deploy-first workflow is a numbered checklist with grant steps and local-dev validation via has_schema_privilege; RLS testing validates with SET ROLE as a non-BYPASSRLS role. Destructive operations (delete project, drop schema, delete branch) are gated on explicit user permission with export-first recovery options A/B, and the Troubleshooting table provides error-to-fix feedback loops, matching the 5 anchor. Not 4 because checkpoints are explicit rather than mostly present.

5 / 5

Progressive Disclosure

Good structure: SKILL.md is an overview plus core workflows, with a 'Reference docs' block giving one-line descriptions of six real reference files (all verified to exist, including deep-linked anchors), and detail (sizing tables, connection patterns, pgvector, off-platform) correctly split out. Minor gaps keep it below 5: references/medallion-from-cdc.md is not reachable from SKILL.md at all (only via lakehouse-sync.md and synced-tables.md, a 2-level chain), and the synced-table grant workflow is inlined in SKILL.md where it arguably belongs in synced-tables.md. Well above 3 since references are clearly signaled and content is appropriately placed.

4 / 5

Total

18

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description with an explicit two-part structure: concrete capability areas followed by clear 'Use when' trigger guidance. Third-person voice, no fluff or over-claims. The only improvement would be adding a few natural synonyms (PostgreSQL, managed/serverless Postgres) and mentioning branching/HA among the capabilities.

DimensionReasoningScore

Specificity

"projects, scaling, connectivity, Lakebase synced tables, and Data API" lists five concrete capability areas with only minor gaps (branching, HA, roles unmentioned), matching the 'several specific actions; minor gaps' anchor. Not a 5 because capabilities are stated as noun-topics rather than concrete actions, and not a 3 because coverage goes well beyond 1-2 items.

4 / 5

Completeness

Explicitly answers both: "Databricks Lakebase Postgres: projects, scaling, connectivity, Lakebase synced tables, and Data API" (what) and "Use when asked about Lakebase databases, OLTP storage, or connecting apps to Postgres on Databricks" (when) with concrete trigger phrases. Clearly matches the 5 anchor rather than 4, where the 'when' would be less specific.

5 / 5

Trigger Term Quality

"Lakebase databases, OLTP storage, or connecting apps to Postgres on Databricks" includes natural phrases a user would say, plus the distinctive product name. A few natural variations are missing (e.g., "PostgreSQL", "managed Postgres", "serverless database"), keeping it below the comprehensive-synonyms 5 anchor.

4 / 5

Distinctiveness Conflict Risk

"Databricks Lakebase Postgres" names a clear niche, and triggers like "Postgres on Databricks" are qualified so they won't fire for generic Postgres or database skills. Minimal conflict risk with the parent databricks skill since the CLI group and product name are distinct.

5 / 5

Total

18

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

databricks/databricks-agent-skills

Path

skills/databricks-lakebase/SKILL.md

Reviewed

Table of Contents

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