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.
86
83%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
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 that clearly identifies its niche (Lakebase Postgres via Databricks CLI) and includes an explicit 'Use when' clause with relevant trigger terms. The main weakness is that the specificity of concrete actions could be improved by listing more granular operations beyond 'manage'. Overall, it performs well for skill selection purposes.
Suggestions
Expand the concrete actions listed beyond 'create, configure, or manage' to include specific operations like 'list projects', 'delete branches', 'scale computes', 'check endpoint status' to improve specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Lakebase Postgres Autoscaling) and some actions (manage projects, branches, endpoints via Databricks CLI), but doesn't list multiple specific concrete actions like 'create project', 'delete branch', 'scale endpoint', etc. in detail. | 2 / 3 |
Completeness | Clearly answers both 'what' (manage Lakebase Postgres Autoscaling projects, branches, and endpoints via Databricks CLI) and 'when' (explicit 'Use when asked to create, configure, or manage Lakebase Postgres databases, projects, branches, computes, or endpoints'). | 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 use. | 3 / 3 |
Distinctiveness Conflict Risk | Very specific niche targeting Lakebase Postgres Autoscaling via Databricks CLI. The combination of 'Lakebase', 'Postgres', and 'Databricks CLI' creates a highly distinct trigger profile unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
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 strong, actionable skill with excellent CLI examples and well-sequenced workflows including validation steps and safety constraints. Its main weakness is that the Schema Permissions section is quite verbose and could benefit from being extracted to a separate file, and some introductory descriptions explain concepts Claude already understands. Overall, it provides high-quality, executable guidance for managing Lakebase Postgres resources.
Suggestions
Extract the 'Schema Permissions for Deployed Apps' section into a separate PERMISSIONS.md file and reference it from the main skill to improve progressive disclosure and reduce inline verbosity.
Trim the introductory paragraph ('Lakebase is Databricks' serverless Postgres-compatible database...') and resource type descriptions (e.g., 'Database: Standard Postgres database within a branch') since Claude understands these concepts.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient and well-structured, but includes some unnecessary explanations (e.g., 'Lakebase is Databricks' serverless Postgres-compatible database (similar to Neon)' and the detailed Schema Permissions section is quite lengthy). The resource hierarchy explanation is useful but the description of what a Project/Branch/Database is could be tighter since Claude understands these concepts. | 2 / 3 |
Actionability | The skill provides fully executable CLI commands with concrete flags, JSON payloads, and profile arguments throughout. Commands are copy-paste ready with clear placeholders, and the CLI discovery pattern (`-h` flags) ensures Claude can dynamically find exact syntax. The troubleshooting table adds practical error-resolution guidance. | 3 / 3 |
Workflow Clarity | Multi-step processes are clearly sequenced with explicit validation checkpoints. The branch deletion workflow has a clear unprotect-then-delete sequence, the app deployment workflow has a numbered correct-workflow sequence with verification steps, and the 'already ran locally first' scenario includes a feedback loop with user confirmation before destructive actions. The warning about never deleting the production branch is a good safety constraint. | 3 / 3 |
Progressive Disclosure | The skill references parent skill 'databricks-core' and 'databricks-apps' skill appropriately, but the Schema Permissions section is very detailed and could be split into a separate reference file. The content is well-organized with clear headers, but the inline depth of the 'What's Next' section (especially the permissions discussion) makes the skill longer than ideal for an overview document. | 2 / 3 |
Total | 10 / 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.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- databricks/devhub
- Commit
6338825
- Reviewed
Table of Contents
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