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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.

90

1.78x
Quality

86%

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

72%

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

A well-structured router skill: concise, well-organized, with real clearly-labeled reference files at one level of depth. Its weakness is that actionable and workflow detail — concrete commands and the full validate/deploy/run sequence with checkpoints — lives mostly in the references rather than the SKILL.md body itself.

Suggestions

Inline one minimal executable end-to-end example (e.g., a tiny databricks.yml snippet plus the 'bundle validate --strict' and 'bundle deploy' commands) so the body is self-sufficient for the common case before readers dive into references.

Make the validate → deploy → run → monitor sequence explicit in the body with numbered steps and validation checkpoints, rather than only summarizing it in the General Guidelines.

Surface at least one concrete pattern from the alerts reference inline (e.g., a minimal alert YAML), since the body flags alerts as critical/API-differing but gives no example to act on immediately.

DimensionReasoningScore

Conciseness

Lean overview that assumes Claude's competence — it never explains what Databricks or a bundle is, and every section (references, when-to-use, guidelines) earns its place without padding.

3 / 3

Actionability

A few concrete specifics appear (the 'bundle validate --strict --target <target>' command, the '<name>.<resource_type>.yml' naming convention), but most executable detail is deferred to reference files rather than given inline, leaving the body itself as a router rather than copy-paste-ready guidance.

2 / 3

Workflow Clarity

The guideline 'Always validate after configuration changes' supplies one checkpoint, but the full validate→deploy→run→monitor sequence is not explicitly sequenced with checkpoints in the body; the feedback loops live in the deploy-and-run reference rather than the main file.

2 / 3

Progressive Disclosure

Clear overview with well-signaled one-level-deep references — each reference file is real, described in one line, and organized by task, with external doc links kept separate; navigation is easy.

3 / 3

Total

10

/

12

Passed

Description

100%

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, concise description: it enumerates concrete capabilities, provides an explicit 'Use when' trigger, names natural user terms (including the former 'Asset Bundles' alias), and occupies a clearly distinct niche. Voice is third-person imperative, consistent with the guidelines.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Create, configure, validate, deploy, run, and manage' — matching the score-3 anchor of enumerating several specific capabilities rather than vague verbs.

3 / 3

Completeness

Explicitly answers both 'what' (the six actions on DABs) and 'when' via an explicit 'Use when working with Databricks resources via DABs...' clause, matching the score-3 anchor.

3 / 3

Trigger Term Quality

Covers natural user terms — 'DABs', 'Databricks Asset Bundles', 'dashboards, jobs, pipelines, alerts, volumes, and apps' — giving good coverage of phrases a user would actually say, including the deprecated name as an alias.

3 / 3

Distinctiveness Conflict Risk

Scoped tightly to Declarative Automation Bundles with Databricks-specific triggers, making it unlikely to fire for unrelated skills; the niche is distinct.

3 / 3

Total

12

/

12

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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