databricks-core
Databricks CLI operations: auth, profiles, data exploration, and bundles. Contains up-to-date guidelines for Databricks-related CLI tasks.
58
66%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./examples/inventory-intelligence/template/.agents/skills/databricks-core/SKILL.mdQuality
Discovery
32%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 identifies a clear domain (Databricks CLI) and lists high-level capability areas, but lacks concrete actions and an explicit 'Use when...' clause. The trigger terms are reasonable but incomplete, and the description would benefit from more specific actions and explicit guidance on when Claude should select this skill.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about Databricks CLI commands, configuring Databricks authentication, deploying Databricks bundles, or exploring Databricks workspace data.'
Replace high-level categories with concrete actions, e.g., 'Configure Databricks authentication profiles, list and query workspace tables, deploy and validate Databricks asset bundles, manage cluster configurations via CLI.'
Include additional natural trigger terms users might say, such as 'databricks workspace', 'dbx', 'databricks jobs', 'databricks deploy', or 'databricks token'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Databricks CLI) and lists some action areas (auth, profiles, data exploration, bundles), but these are categories rather than concrete actions. It doesn't specify what exactly is done within each area (e.g., 'configure authentication tokens', 'deploy bundles', 'query tables'). | 2 / 3 |
Completeness | Describes what it does (Databricks CLI operations) but has no explicit 'Use when...' clause or equivalent trigger guidance. Per the rubric, a missing 'Use when...' clause should cap completeness at 2, and since the 'what' is also somewhat vague, this scores a 1. | 1 / 3 |
Trigger Term Quality | Includes relevant keywords like 'Databricks', 'CLI', 'auth', 'profiles', 'bundles', and 'data exploration', which users might naturally say. However, it misses common variations like 'databricks-cli', 'dbx', 'workspace', 'jobs', 'deploy', or 'databricks connect'. | 2 / 3 |
Distinctiveness Conflict Risk | The Databricks CLI focus is fairly niche and unlikely to conflict with most skills, but the mention of 'data exploration' is broad enough to potentially overlap with general data analysis or database skills. Adding more Databricks-specific triggers would improve distinctiveness. | 2 / 3 |
Total | 7 / 12 Passed |
Implementation
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is an excellent skill file that serves as a well-structured hub for Databricks CLI operations. It is concise, highly actionable with executable commands and explicit anti-patterns, has clear workflow sequencing with validation checkpoints, and uses progressive disclosure effectively to point to specialized skills and reference files. The shell session behavior warning and positional-vs-flag argument distinctions are particularly valuable additions that prevent common errors.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient throughout. It avoids explaining what Databricks is, what CLI tools are, or other concepts Claude already knows. Every section delivers actionable information without padding, and the anti-pattern examples (❌ WRONG) earn their tokens by preventing common errors. | 3 / 3 |
Actionability | The skill provides fully executable, copy-paste-ready CLI commands with correct syntax, including positional vs flag argument distinctions. The troubleshooting table, anti-pattern examples, and shell session behavior warnings are all concrete and immediately actionable. | 3 / 3 |
Workflow Clarity | The workflow is clearly sequenced: check CLI installation → authenticate → select profile → execute commands. The prerequisites section has explicit stop-and-redirect checkpoints (e.g., 'STOP. Do not proceed' if CLI is missing). The profile selection section enforces a critical validation step. The Claude Code section explicitly addresses a shell session pitfall with working vs non-working examples. | 3 / 3 |
Progressive Disclosure | The skill serves as a clear hub/overview with well-signaled one-level-deep references to dedicated skills (databricks-jobs, databricks-pipelines, etc.) and reference files (CLI Installation, CLI Authentication, Data Exploration). The 'Required Reading by Task' table provides excellent navigation. Content is appropriately split between the overview and referenced files. | 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.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- databricks/devhub
- Commit
0b6297e
- Reviewed
Table of Contents
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