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databricks-core

Databricks CLI operations and the parent/entry-point skill for Databricks CLI use: authentication, profile selection, and bundles. Load this first for CLI, auth, profile, and bundle tasks, then load the matching product skill. For finding or exploring data, answering questions about the data, or generating SQL, load the databricks-data-discovery skill (it routes to Genie One). Contains up-to-date guidelines for Databricks-related CLI tasks.

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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.

A highly actionable, well-sequenced CLI entry-point skill whose quick reference, error tables, and STOP-gated setup flow are exemplary. Its two real weaknesses are progressive disclosure (all three referenced detail files are missing from the bundle) and modest duplication in the data-discovery routing sections.

Suggestions

Ship the three referenced files (databricks-cli-install.md, databricks-cli-auth.md, manual-data-exploration.md) in the bundle, or remove the links — every detailed-guidance pointer in the body currently resolves to nothing.

Consolidate the duplicated databricks-data-discovery routing (explained in both the 'Product Skills' and 'Data Exploration' sections) into a single routing rule to save tokens.

Define or link the '/databricks-dabs' path invoked in the 'Required Reading by Task' table so the deploy route is followable.

DimensionReasoningScore

Conciseness

The body is command-dense and imperative — quick-reference blocks, error tables, and CRITICAL warnings all earn their tokens. Minor over-explanation could be trimmed: the data-discovery routing is explained twice ("Product Skills" and "Data Exploration" sections), the reference guides are listed in both "Required Reading by Task" and "Reference Guides", and lines like "A CLI that is present but too old is not 'good enough' — it must be upgraded, not worked around" restate the adjacent STOP instruction. Not 5 due to this duplication; not 3 because the padding is minor relative to the volume of concrete guidance.

4 / 5

Actionability

Fully executable throughout: complete commands with --profile flags ("databricks apps list --profile my-workspace"), explicit CORRECT vs. WRONG positional-argument examples with the failing variants crossed out, exact error strings mapped to fixes ("cannot configure default credentials" → "Use --profile flag or authenticate first"), an exact signup URL, and concrete env-var fallback (DATABRICKS_HOST/DATABRICKS_TOKEN). The harness-specific shell-session example (WORKS/DOES NOT WORK) is copy-paste ready.

5 / 5

Workflow Clarity

Sequenced setup workflow with an explicit validation gate ("Run the floor check... If it reports UPGRADE or INSTALL: STOP"), numbered profile-selection steps with the NEVER-auto-select rule, and a troubleshooting table serving as an error-recovery feedback loop. Minor gaps: the deploy row routes to "/databricks-dabs" which is undefined here, and there is no explicit post-auth verification step. Not 5 because checkpoints are spread across sections rather than a unified flow and one route dangles; not 3 because validation checkpoints and error recovery are explicitly present.

4 / 5

Progressive Disclosure

The SKILL.md itself is well structured as an overview with clearly signaled one-level references ([CLI Installation](databricks-cli-install.md), [CLI Authentication](databricks-cli-auth.md), [Manual Data Exploration](manual-data-exploration.md)) and a task→reading table. However, none of those three referenced files exist in the bundle (no references/ directory; the only bundle files are unreferenced assets databricks.png/databricks.svg), so every detailed-content pointer dangles and navigation dead-ends. Not 4 because the bundle structure doesn't back the reference scheme; not 2 because the body is genuinely well sectioned and references are prominently signaled, not buried or replaced by inlined bulk content.

3 / 5

Total

16

/

20

Passed

Description

78%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 entry-point description: it states concrete capabilities, gives explicit load-first trigger guidance, and actively manages routing boundaries with sibling product skills. Its main weaknesses are a filler closing sentence ("Contains up-to-date guidelines for Databricks-related CLI tasks") and missing a few natural trigger terms users would say.

DimensionReasoningScore

Specificity

Names the domain ("Databricks CLI operations") and several concrete capabilities ("authentication, profile selection, and bundles") plus explicit routing to product skills and databricks-data-discovery — several specific actions with minor gaps (e.g., resource listing/deploy operations are only implied). The trailing "Contains up-to-date guidelines for Databricks-related CLI tasks" is filler but doesn't dominate. Not 5 because coverage of what the CLI operations actually cover is thinner than the routing detail; not 3 because multiple concrete actions are explicitly listed.

4 / 5

Completeness

Both parts are explicit: what — "Databricks CLI operations... authentication, profile selection, and bundles"; when — "Load this first for CLI, auth, profile, and bundle tasks, then load the matching product skill". The when-clause is direct trigger guidance with concrete task types, but it doesn't include "user mentions X" phrasing or cover the data-discovery triggers as symmetrically as the anchor-5 example. Not 3 because the when is explicitly stated, not merely implied; not 5 because the when could be more specific about user-mention triggers.

4 / 5

Trigger Term Quality

Natural phrases a Databricks user would say appear throughout: "CLI", "auth", "profile", "bundle", "finding or exploring data", "answering questions about the data", "generating SQL", with synonyms (auth/authentication). Good coverage but missing common variations like "workspace", "deploy", "jobs", or "Unity Catalog". Not 5 because a few natural terms users say for this entry-point role are absent; not 3 because coverage goes well beyond a single generic keyword.

4 / 5

Distinctiveness Conflict Risk

Positions itself precisely as "the parent/entry-point skill for Databricks CLI use" with explicit routing rules ("then load the matching product skill"; data questions route to databricks-data-discovery), which resolves overlap with the child product skills it names. Clear niche with distinct triggers and minimal conflict risk.

5 / 5

Total

17

/

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/databricks-agent-skills

Path

skills/databricks-core/SKILL.md

Reviewed

Table of Contents

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