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databricks-dabs

Create, configure, validate, deploy, run, and manage Declarative Automation Bundles (DABs, formerly Databricks Asset Bundles). Use when working with Databricks resources via DABs including dashboards, jobs, pipelines, alerts, volumes, and apps.

92

1.78x
Quality

89%

Does it follow best practices?

Impact

98%

1.78x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

86%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.

Well-structured, lean overview skill that effectively uses progressive disclosure to route detail into reference files. The main improvement would be inlining a short executable deploy/run sequence with an explicit feedback loop.

Suggestions

Add a brief inline sequenced workflow (validate -> deploy -> run) with an explicit error-recovery loop, rather than only delegating it to references/deploy-and-run.md.

Include one or two copy-paste-ready command examples (e.g., a minimal `bundle deploy --target dev`) alongside the existing validate command to lift actionability.

Tighten the General Guidelines parentheticals (e.g., "(see Bundle Structure reference)") into compact cross-links so every token earns its place.

DimensionReasoningScore

Conciseness

Lean body with no padding: an overview, a one-line-per-file reference list, a bullet 'when to use' section, six terse guidelines, and external doc links. It does not explain what DABs or Databricks is.

5 / 5

Actionability

Provides a concrete command ("bundle validate --strict --target <target>") and naming convention ("<name>.<resource_type>.yml"), but most executable detail is delegated to reference files rather than copy-paste-ready inline examples.

4 / 5

Workflow Clarity

An explicit validation checkpoint is stated ("Always validate after configuration changes") with the matching command, but the full validate→deploy→run→monitor sequence is delegated to a reference rather than sequenced inline with error-recovery loops.

4 / 5

Progressive Disclosure

Clear overview pointing to five well-signaled, one-level-deep reference files (all verified to exist) each with a descriptive one-liner, plus external documentation links — easy to navigate.

5 / 5

Total

18

/

20

Passed

Description

92%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, specific description that clearly states capabilities and explicit trigger conditions with named resource types. Only minor gap is the absence of file-extension/synonym triggers like databricks.yml.

DimensionReasoningScore

Specificity

Lists six concrete actions (create, configure, validate, deploy, run, manage) plus named resource types (dashboards, jobs, pipelines, alerts, volumes, apps), giving comprehensive coverage.

5 / 5

Completeness

Explicitly answers both 'what' (create/configure/validate/deploy/run/manage DABs) and 'when' ("Use when working with Databricks resources via DABs including...") with concrete trigger phrases.

5 / 5

Trigger Term Quality

Good natural-term coverage (Databricks resources, DABs, and the resource-type names), but lacks synonyms and file extensions (e.g., databricks.yml, bundle YAML) that users might say.

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche (Declarative Automation Bundles / Databricks) with distinct triggers and named resource types, minimizing overlap with other skills.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
databricks/databricks-agent-skills
Reviewed

Table of Contents

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