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databricks-apps

Build apps on Databricks Apps platform. Use when asked to create data apps, analytics tools, or custom interactive visualizations. A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, not this skill. Evaluates data access patterns (analytics vs Lakebase synced tables) before scaffolding. Invoke BEFORE starting implementation.

69

Quality

86%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is databricks-apps in databricks/databricks-agent-skills

SKILL.md
Quality
Evals
Security

Quality

Content

86%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 well-structured, highly actionable guide: executable commands, an ordered workflow with a mandatory decision gate, and clean progressive disclosure into verified reference files. Its main weakness is mild redundancy (repeated naming rules, overlap between the decision gate and routing table) and a missing explicit validate→retry loop.

Suggestions

Consolidate the app-name rule (≤26 chars, lowercase letters/numbers/hyphens) into a single canonical location and reference it, instead of restating it in Generic Guidelines, the Scaffolding step, and Directory Naming.

Add an explicit validate→fix→re-validate feedback loop to the Analytics development workflow (e.g. 'If validate fails, review errors, fix, and re-run validate before proceeding').

Reconcile the Data Access Decision Gate table and the 'When to Use What' routing list so each pattern is defined once and the other cross-references it, reducing overlap.

DimensionReasoningScore

Conciseness

Information-dense with terse bullets and tables, and it assumes Claude's competence (no padding about what Databricks or React are). Minor redundancy holds it below 5: the ≤26-char lowercase-hyphen app-name rule is repeated in three places, and the Decision Gate table overlaps with the 'When to Use What' routing list.

4 / 5

Actionability

Provides copy-paste-ready, executable commands throughout ('databricks apps init --name … --features … --set …', 'npm run typegen', 'databricks apps validate --profile <PROFILE>', 'npx @databricks/appkit docs') plus a wrong-vs-right scaffolding example covering the common mistake.

5 / 5

Workflow Clarity

Clear ordered sequencing ('FOLLOW THIS ORDER'), a mandatory Data Access Decision Gate checkpoint, numbered analytics steps 1–6 with a typegen 'verify all queries show ✓' checkpoint, validate-before-deploy, and post-deploy verification. Held below 5 by the absence of an explicit validate→fix→re-validate feedback loop in the main analytics workflow.

4 / 5

Progressive Disclosure

SKILL.md is an overview pointing to ~16 real one-level-deep reference files via a 'Required Reading by Phase' table and 'When to Use What' routing; content is appropriately split with easy navigation and no nested reference chains.

5 / 5

Total

18

/

20

Passed

Description

87%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 is strong: it states concrete actions, gives natural trigger phrases, answers both what and when, and proactively distinguishes itself from a competing dashboard skill. Minor specificity gaps stem from not listing the full plugin/feature surface.

DimensionReasoningScore

Specificity

Names the domain and several concrete actions ('Build apps', 'Evaluates data access patterns (analytics vs Lakebase synced tables) before scaffolding'), but does not enumerate the full range of capabilities (Genie, Model Serving, agents, jobs) the skill covers.

4 / 5

Completeness

Explicitly answers both what ('Build apps on Databricks Apps platform') and when ('Use when asked to create data apps, analytics tools, or custom interactive visualizations') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Includes natural phrases users would say ('create data apps', 'analytics tools', 'custom interactive visualizations', 'create a dashboard'); coverage is good but a few natural synonyms are missing.

4 / 5

Distinctiveness Conflict Risk

Actively disambiguates from a sibling skill ('A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, not this skill'), establishing a clear niche with minimal conflict risk.

5 / 5

Total

18

/

20

Passed

Validation

81%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 27 deeper-than-1-level

Warning

referenced_paths_exist

Referenced path issues: 27 deeper-than-1-level

Warning

Total

13

/

16

Passed

Repository
databricks/databricks-agent-skills
Reviewed

Table of Contents

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