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databricks-lakebase

Manage Lakebase Postgres Autoscaling projects, branches, and endpoints via Databricks CLI. Use when asked to create, configure, or manage Lakebase Postgres databases, projects, branches, computes, or endpoints.

68

Quality

83%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

This is a well-structured, highly actionable skill that provides concrete CLI commands for managing Lakebase Postgres resources. Its main strengths are executable examples with proper flags/JSON and clear multi-step workflows with validation. Minor weaknesses include some unnecessary explanatory text and a somewhat long single-file structure that could benefit from splitting advanced topics into referenced files.

Suggestions

Trim explanatory text like the Lakebase product description and basic definitions (e.g., 'Standard Postgres database within a branch') that Claude already understands.

Consider splitting the 'What's Next' section (app scaffolding, read replicas, role management) into a separate reference file to keep the main SKILL.md focused on core CRUD operations.

DimensionReasoningScore

Conciseness

Generally efficient but includes some unnecessary explanation (e.g., 'Lakebase is Databricks' serverless Postgres-compatible database (similar to Neon)' and the description of what branches/endpoints/databases are). The resource hierarchy section is useful but some definitions explain concepts Claude would know (e.g., 'Standard Postgres database within a branch'). The overall structure is reasonably tight but could be trimmed.

2 / 3

Actionability

Provides fully executable CLI commands with concrete flags, JSON payloads, and profile arguments throughout. Commands are copy-paste ready with clear placeholder conventions. The 'CLI Discovery' section reinforces using `-h` for exact syntax, and every workflow includes specific runnable commands.

3 / 3

Workflow Clarity

Multi-step processes are clearly sequenced (e.g., create project → verify resources, unprotect → delete branch, discover branch → discover database → scaffold app). Validation steps are present (verify auto-provisioned resources after creation, check branch state before deletion). The protected branch deletion workflow includes an explicit two-step sequence with safety guidance ('Never delete the production branch').

3 / 3

Progressive Disclosure

References the parent 'databricks-core' skill and the 'databricks-apps' skill appropriately, but there are no bundle files to offload detailed content to. The resource name formats table and troubleshooting table are inline, which is fine for this length, but the document is fairly long (~130 lines of content) and could benefit from splitting advanced workflows (app scaffolding, read replicas, role management) into separate files.

2 / 3

Total

10

/

12

Passed

Description

89%

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

This is a solid skill description with clear 'what' and 'when' clauses, strong trigger terms specific to the Lakebase/Databricks ecosystem, and excellent distinctiveness. The main weakness is that the capability actions are somewhat general ('manage', 'configure') rather than listing specific concrete operations, which keeps specificity from reaching the top score.

Suggestions

List more specific concrete actions beyond 'manage' — e.g., 'create and delete projects, create and reset branches, start/stop/scale computes, configure endpoints' to improve specificity.

DimensionReasoningScore

Specificity

Names the domain (Lakebase Postgres Autoscaling) and some actions (manage projects, branches, endpoints via Databricks CLI), but doesn't list specific concrete actions beyond 'manage' — e.g., doesn't detail operations like 'create branch', 'scale compute', 'list endpoints' individually.

2 / 3

Completeness

Clearly answers both 'what' (manage Lakebase Postgres Autoscaling projects, branches, and endpoints via Databricks CLI) and 'when' (Use when asked to create, configure, or manage Lakebase Postgres databases, projects, branches, computes, or endpoints). Explicit 'Use when' clause is present.

3 / 3

Trigger Term Quality

Includes strong natural keywords users would say: 'Lakebase', 'Postgres', 'Databricks CLI', 'projects', 'branches', 'computes', 'endpoints', 'databases', 'create', 'configure', 'manage'. Good coverage of terms a user working with this specific tooling would naturally use.

3 / 3

Distinctiveness Conflict Risk

Very specific niche — Lakebase Postgres Autoscaling via Databricks CLI is a highly distinct domain. Unlikely to conflict with generic database skills or other CLI tools due to the specific product naming.

3 / 3

Total

11

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

10

/

11

Passed

Repository
databricks/devhub
Reviewed

Table of Contents

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