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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.

72

Quality

90%

Does it follow best practices?

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SecuritybySnyk

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SKILL.md
Quality
Evals
Security

Quality

Content

92%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.

An excellent, highly actionable skill body: executable commands, gated multi-step workflows with validation, and clean one-level-deep references that all resolve to real files. The lone weakness is mild redundancy across the disambiguation and 'ask the user' guidance, which keeps conciseness at 4 rather than 5.

DimensionReasoningScore

Conciseness

Dense with high-value, directive gotchas (smoke-test selector rules, AppKit version pinning, TypeScript cast rules) and assumes Claude knows the frameworks; held below 5 by noticeable redundancy — the AI/BI-vs-app disambiguation and the 'ask the user, don't silently create' guidance recur across several sections.

4 / 5

Actionability

Copy-paste-ready commands cover the common cases end to end ('databricks apps manifest', 'databricks apps init --name ... --features ... --set ...', 'npm run typegen', 'databricks apps validate --profile <PROFILE>', 'npx @databricks/appkit docs'), plus a concrete project-structure map and a worked WRONG/CORRECT scaffolding example.

5 / 5

Workflow Clarity

Sequenced workflows with explicit validation checkpoints: the Analytics app flow (create SQL → typegen verify ✓ → read types → write App.tsx → update selectors → validate) and the Genie/scaffolding flows each number steps and gate on validation ('DO NOT write UI code before running typegen', validate before deploy).

5 / 5

Progressive Disclosure

A 'Required Reading by Phase' table plus inline links push detail to one-level-deep reference files (references/appkit/*.md, references/platform-guide.md, references/other-frameworks.md), and every referenced path resolves to a real bundle file — clear overview with well-signaled, navigable references.

5 / 5

Total

19

/

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.

A strong, specific description that answers both what and when while proactively disambiguating from a sibling dashboard skill. The only real weakness is mixed imperative/second-person voice ('Use when', 'Invoke'), which the rubric penalizes on specificity.

DimensionReasoningScore

Specificity

Lists several concrete actions ('Build apps on Databricks Apps platform', 'create data apps, analytics tools, or custom interactive visualizations', 'Evaluates data access patterns (analytics vs Lakebase synced tables) before scaffolding'), giving strong coverage; held below 5 because the voice mixes imperative/second-person ('Use when', 'Invoke BEFORE'), which the rubric penalizes specificity for by 1.

4 / 5

Completeness

Clearly states the 'what' ('Build apps on Databricks Apps platform') and an explicit 'when' with concrete triggers ('Use when asked to create data apps, analytics tools, or custom interactive visualizations. ... Invoke BEFORE starting implementation.'), plus disambiguation guidance.

5 / 5

Trigger Term Quality

Good natural-keyword coverage ('data apps', 'analytics tools', 'custom interactive visualizations', 'dashboard', 'create a dashboard'), matching the 'good coverage, a few natural terms missing' anchor; not a 5 because it lacks the full synonym/extension spread the top anchor exemplifies.

4 / 5

Distinctiveness Conflict Risk

Explicitly carves out a niche and avoids the wrong-skill trap ('A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, not this skill'), giving 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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