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databricks-serverless-migration

Migrate Databricks workloads from classic compute to serverless compute. Scans code for serverless compatibility issues, provides concrete fixes for the serverless Spark Connect architecture, and guides the full migration to serverless environments. Use for classic-to-serverless migrations, serverless code compatibility checks, or writing new serverless-compatible notebooks and jobs. Not for classic DBR version upgrades or cluster configuration changes within classic compute.

72

Quality

91%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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

SKILL.md
Quality
Evals
Security

Quality

Content

81%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 content is highly actionable and the migration workflow is exceptionally well structured with validation, feedback loops, and deliverables. The main weakness is redundancy: the Quick Fixes section duplicates Step 2's fix tables, which in turn overlap the reference files, inflating the token cost of an otherwise excellent skill.

Suggestions

Deduplicate the Quick Fixes Reference against Step 2's Category A–G tables: keep the concise pattern→fix tables in Step 2 and move the worked before/after code examples entirely into references/code-patterns.md, linking to them instead.

Trim prose that restates adjacent tables, e.g. the sentence explaining the test/production branch purposes duplicates the two-branch strategy table above it.

Consider moving the Failure Reporting Protocol and Performance Mode Selection sections into a reference file, keeping only the trigger conditions and the user-facing message inline.

DimensionReasoningScore

Conciseness

The body is dense with genuinely non-obvious, specific content and avoids explaining concepts Claude already knows, but the ~150-line Quick Fixes Reference substantially repeats Step 2's Category A–G fix tables (RDD rewrites, streaming triggers, caching removal all appear twice), and prose like 'The test branch is a safe sandbox for experimentation; the production branch contains only the changes that production actually needs' restates the adjacent table. Not a 2 because the padding is duplication rather than concept explanation, and most tokens carry unique information.

3 / 5

Actionability

Fully executable throughout: copy-paste before/after code blocks for every major pattern, exact error-message-to-fix mappings (e.g., 'INFINITE_STREAMING_TRIGGER_NOT_SUPPORTED' → 'Add .trigger(availableNow=True)'), a concrete Jobs API environments JSON block, and branch naming patterns with timestamps. Not below 5 because the common cases are covered with ready-to-run code.

5 / 5

Workflow Clarity

The 4-step lifecycle (Ingest → Analyze → Test → Validate) is explicitly sequenced with validation checkpoints: pre-run static scanning, A/B comparison with executable assertions, a 'Should This Change Go to Production?' decision table, feedback loops ('If it fails, get the error output, debug, fix, and retry'), stopping conditions, and a deliverables checklist ('If any deliverable is missing, the migration is incomplete').

5 / 5

Progressive Disclosure

All five referenced files exist, are one level deep, and are well signaled both inline at point of use and in a dedicated Reference Guides section with one-line descriptions. Not a 5 because the ~640-line body inlines substantial detail (full Category A–G compatibility tables, Failure Reporting Protocol, Performance Mode Selection) that overlaps content already carried in references/compatibility-checks.md and references/code-patterns.md, so the split is not as clean as a lean overview pointing to detail files.

4 / 5

Total

17

/

20

Passed

Description

100%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 excellent: it states concrete capabilities in third person, provides explicit 'Use for' trigger phrases, and adds a 'Not for' clause that cleanly delineates scope. It directly matches the strongest reference examples in the rubric.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — 'Migrate Databricks workloads from classic compute to serverless compute', 'Scans code for serverless compatibility issues', 'provides concrete fixes for the serverless Spark Connect architecture', and 'guides the full migration' — covering scanning, fixing, migrating, and authoring new serverless code comprehensively.

5 / 5

Completeness

It explicitly answers both questions: what ('Scans code for serverless compatibility issues, provides concrete fixes... and guides the full migration') and when ('Use for classic-to-serverless migrations, serverless code compatibility checks, or writing new serverless-compatible notebooks and jobs'), matching the top anchor exactly.

5 / 5

Trigger Term Quality

Natural user phrasings are comprehensively covered: 'classic-to-serverless migrations', 'serverless code compatibility checks', 'serverless-compatible notebooks and jobs', plus domain synonyms like 'classic compute', 'serverless compute', and 'Spark Connect'. Not below 5 because no common natural term for this niche is missing.

5 / 5

Distinctiveness Conflict Risk

A clear niche (Databricks classic-to-serverless migration) with an explicit negative scope ('Not for classic DBR version upgrades or cluster configuration changes within classic compute') that sharply reduces overlap with adjacent skills. Not below 5 since conflict risk is minimal.

5 / 5

Total

20

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (648 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

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

Warning

Total

14

/

16

Passed

Repository

databricks/devhub

Path

.databricks/aitools/skills/databricks-serverless-migration/SKILL.md

Reviewed

Table of Contents

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