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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.

57

Quality

72%

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tessl review fix ./.agents/skills/databricks-core/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

78%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.

The body is a strong, executable CLI reference: concrete commands, explicit anti-patterns, troubleshooting, and gated setup steps with real checkpoints. Its two weaknesses are a deploy workflow that never explicitly sequences validation before deploy, and a progressive-disclosure layer whose four referenced detail files do not exist in the bundle, leaving the deepest guidance unreachable. Conciseness is good with only minor duplication between the reading-table and reference-list sections.

Suggestions

Add the four referenced files (databricks-cli-install.md, databricks-cli-auth.md, data-exploration.md, declarative-automation-bundles.md) to the bundle, or move their content inline — currently every 'Read BEFORE proceeding' link points to a file that doesn't exist, breaking the skill's own gating rules.

Make the deploy sequence explicit with a validation gate: '1. databricks bundle validate --profile <PROFILE> 2. Only when valid: databricks bundle deploy -t <TARGET> --profile <PROFILE>' in the Quick Reference's bundles section.

Merge the 'Reference Guides' bullet list into the 'Required Reading by Task' table to remove the duplicate listing of the same four files and free tokens for the missing deploy-validation step.

DimensionReasoningScore

Conciseness

The body is a dense command reference with no concept re-explanations — it assumes Claude's competence throughout ('NEVER auto-select a profile', works/doesn't-work shell patterns). Not score 5 because of mild redundancy: the four reference files are listed twice (in 'Required Reading by Task' and again in 'Reference Guides'), and profile-selection guidance repeats the prerequisites section's auth profiles step. Not score 3 because every section carries non-obvious, task-critical information.

4 / 5

Actionability

Fully executable, copy-paste-ready commands with explicit placeholders for every common case: listing, getting details, UC positional-argument examples, bundle lifecycle, and AI-tools queries. It goes beyond happy-path instructions by showing anti-examples ('❌ WRONG: these flags/commands DON'T EXIST'), a troubleshooting table mapping real error strings to fixes, and a 'check --help when in doubt' fallback. This matches the anchor for executable commands covering the common cases.

5 / 5

Workflow Clarity

The setup workflow has explicit checkpoints: version check with a hard STOP gate ('If the CLI is missing or outdated... STOP'), auth verification, and a gated 4-step profile-selection sequence that requires user confirmation. Not score 5 because deploy ('databricks bundle deploy') lacks an explicit validate-before-deploy checkpoint in sequence — 'bundle validate' appears only as a bare command in the Quick Reference, and the guidance for deploy-time validation is delegated to a reference file. Not score 3 because validation gates are present and explicit for the risky setup steps.

4 / 5

Progressive Disclosure

The structure itself is good — a task-routed 'Required Reading by Task' table plus one-level-deep markdown links — but all four referenced files (databricks-cli-install.md, databricks-cli-auth.md, data-exploration.md, declarative-automation-bundles.md) are absent from the bundle (no references/ directory or matching files exist anywhere), so every deep-dive link dead-ends and the disclosure chain is broken. Not score 4 because navigation to detail content actually fails; not score 2 because the in-body overview is well organized and the reference intent is clearly signaled.

3 / 5

Total

16

/

20

Passed

Description

53%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.

The description names a distinct, well-scoped domain and its main capability areas, but reads as a topic listing rather than an action description, and provides no 'Use when...' trigger guidance at all. The second sentence adds padding ('up-to-date guidelines') without conveying capability or timing. It lands at the middle of the scale: clearly better than generic filler, but below the good examples that pair concrete actions with explicit trigger phrases.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user mentions Databricks, workspaces, Unity Catalog tables, or running Databricks CLI commands' — this alone lifts completeness from 3 to 5.

Rewrite capability areas as concrete actions with verbs, e.g. 'Authenticates and manages CLI profiles, explores catalogs/schemas/tables via AI tools, and deploys Databricks asset bundles' instead of the noun list 'auth, profiles, data exploration, and bundles'.

Delete the filler sentence 'Contains up-to-date guidelines for Databricks-related CLI tasks' and use the freed tokens for natural synonyms (workspace, tables, jobs, bundles) that users actually say when they need this skill.

DimensionReasoningScore

Specificity

Names the domain ('Databricks CLI') and lists four capability areas ('auth, profiles, data exploration, and bundles'), but these are noun-phrase topic labels under the generic wrapper 'operations' rather than concrete actions like 'extract' or 'fill'. Not score 4 because no specific action verbs are given; not score 2 because the domain and sub-domains are clearly named, unlike the minimal 'Processes PDF files' example.

3 / 5

Completeness

Has a clear 'what' (CLI operations across auth, profiles, data exploration, bundles) but no 'when' — there is no 'Use when...' clause or equivalent trigger guidance anywhere; the second sentence ('Contains up-to-date guidelines for Databricks-related CLI tasks') is filler, not usage timing. Per the judging guideline, a missing 'Use when' clause caps completeness at 3.

3 / 5

Trigger Term Quality

Includes genuinely natural terms ('Databricks', 'CLI', 'auth', 'profiles', 'data exploration', 'bundles') that users would say, but misses common variations and synonyms such as 'workspace', 'Unity Catalog', 'tables', or 'jobs'. Not score 4 because keyword coverage is partial rather than 'good' with only a few gaps.

3 / 5

Distinctiveness Conflict Risk

'Databricks CLI operations' carves a clear niche with minimal conflict risk against unrelated skills. Not score 5 because it risks overlapping with the closely related sibling skills the body defers to (databricks-jobs, databricks-pipelines, databricks-apps, databricks-lakebase), none of which the description distinguishes itself from.

4 / 5

Total

13

/

20

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 11 missing

Warning

Total

15

/

16

Passed

Repository

databricks/devhub

Path

.agents/skills/databricks-core/SKILL.md

Reviewed

Table of Contents

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