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databricks-core

Databricks CLI operations: auth, profiles, data exploration, and bundles. Contains up-to-date guidelines for Databricks-related CLI tasks.

55

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The body is highly actionable with executable commands and explicit setup validation, but time-sensitive version numbers and a missing validate->fix->retry loop for destructive bundle deploys hold back conciseness and workflow clarity. Progressive disclosure is well-structured on the page, but the four referenced files are absent from the bundle, breaking the navigation.

Suggestions

Add an explicit validate->fix->retry loop for bundle deploys (e.g., run `bundle validate`, on failure review errors and fix, re-validate, and only then `bundle deploy`).

Move the hard-coded version threshold (v0.292.0) into a version-compatibility/deprecated section, or phrase it as 'run `databricks --version` and ensure it is current' to avoid time-sensitive decay.

Ship the four referenced files (databricks-cli-install.md, databricks-cli-auth.md, data-exploration.md, declarative-automation-bundles.md) in the bundle so the progressive-disclosure links resolve.

DimensionReasoningScore

Conciseness

The body is largely lean and command-focused without explaining concepts Claude already knows, but time-sensitive version numbers appear outside a deprecated section (">= v0.292.0", "< v0.292.0"), which the guidelines say should penalize conciseness. Not a 3 because of this version-specific time-sensitive info; not a 1 because it stays mostly efficient and assumes Claude's competence.

2 / 3

Actionability

Commands are fully executable and copy-paste ready, e.g. "databricks experimental aitools tools discover-schema catalog.schema.table --profile <PROFILE>" and "databricks bundle deploy -t <TARGET> --profile <PROFILE>", plus "WRONG" examples of nonexistent commands — matching score-3 "Fully executable code/commands; specific examples."

3 / 3

Workflow Clarity

The Prerequisites flow has explicit validation ("Run `databricks --version`", "STOP. Do not proceed") and the troubleshooting table provides error-to-solution recovery, but the destructive `bundle deploy` operation lists `bundle validate` and `bundle deploy` with no validate->fix->retry feedback loop, which per the guidelines caps workflow clarity at 2. Not a 3 because of this missing loop; not a 1 because setup validation is explicit.

2 / 3

Progressive Disclosure

The body is well-organized as an overview with clearly signaled one-level-deep references (the "Required Reading by Task" table, "Reference Guides" list, inline links like "[CLI Installation](databricks-cli-install.md)"), but the referenced files do not exist in any bundle directory, so the links resolve to nothing. Not a 3 because the bundle structure does not back the references; not a 1 because the in-document organization is good rather than a monolithic wall of text.

2 / 3

Total

9

/

12

Passed

Description

60%

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

The description clearly states what the skill does with specific concrete operations and natural Databricks terms, but it omits any explicit "Use when..." trigger guidance, capping completeness. It is somewhat distinguishable yet risks overlap with sibling Databricks product skills due to its broad framing.

Suggestions

Add an explicit 'Use when...' clause naming natural triggers (e.g., 'Use when the user needs to authenticate, manage profiles, explore data, or work with bundles via the Databricks CLI') to satisfy the 'when' half of completeness.

Broaden trigger-term coverage with common variations users would say (e.g., 'Databricks', 'Databricks CLI', 'explore tables', 'Databricks auth') rather than a single form of each term.

Disambiguate from sibling product skills by stating what this core skill covers versus what databricks-jobs/pipelines/apps handle.

DimensionReasoningScore

Specificity

The phrase "auth, profiles, data exploration, and bundles" enumerates four distinct concrete CLI operation areas, matching the score-3 anchor "Lists multiple specific concrete actions." It is not a 2 because it goes beyond naming a domain with partial actions to listing multiple specific operations.

3 / 3

Completeness

"Databricks CLI operations: auth, profiles, data exploration, and bundles" answers the "what", but "Contains up-to-date guidelines for Databricks-related CLI tasks" only restates the what with no "when" — there is no "Use when..." clause, which per the guidelines caps completeness at 2. Not a 1 because the what is clearly stated; not a 3 because explicit trigger guidance is absent.

2 / 3

Trigger Term Quality

"Databricks CLI operations", "auth", "profiles", "data exploration", and "bundles" are relevant natural terms, but only one form of each is given without common variations, matching score-2 "Some relevant keywords but missing common variations." Not a 3 because it lacks the breadth of natural-term variations (e.g., "Databricks", "explore tables", "Databricks auth") shown in the score-3 example.

2 / 3

Distinctiveness Conflict Risk

"Databricks CLI operations" is Databricks-specific and unlikely to conflict with non-Databricks skills, but the broad framing could overlap with sibling Databricks product skills (jobs, pipelines, apps, lakebase), matching score-2 "Somewhat specific but could still overlap with similar skills." Not a 3 because no explicit triggers disambiguate it from those siblings.

2 / 3

Total

9

/

12

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 11 missing

Warning

Total

15

/

16

Passed

Repository
databricks/devhub
Reviewed

Table of Contents

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