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databricks-python-sdk

Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.

64

Quality

77%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

High

Do not use without reviewing

Fix and improve this skill with Tessl

tessl review fix ./databricks-skills/databricks-python-sdk/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A highly actionable, code-rich reference with excellent executable examples and a valuable async-pattern section. It is weakened by a monolithic inline structure that should be split into reference files and by missing validation checkpoints around destructive operations.

Suggestions

Move the per-service 'Core API Reference' code blocks into a bundled reference file (e.g. references/api-reference.md) and keep SKILL.md as an overview with one-level-deep pointers, improving both conciseness and progressive disclosure.

Remove the 'Quick Reference Links' table (or the per-section Doc: lines) to eliminate duplicated URL content and reduce token cost.

Add explicit validation/error-recovery steps for destructive or long-running operations (e.g., verify a cluster is RUNNING after create_and_wait, confirm delete succeeded) to strengthen workflow clarity.

DimensionReasoningScore

Conciseness

Individual sections are lean (mostly executable code with one-line comments), but the body is ~620 lines with ~400 lines of inline API reference that could live in a reference file, and the 'Quick Reference Links' table duplicates doc URLs already shown per section, fitting the 'could be tightened' anchor rather than the lean level 3.

2 / 3

Actionability

Nearly every section provides complete, copy-paste-ready executable code (clusters, jobs, SQL, Unity Catalog, files, serving, the async asyncio.to_thread pattern), with specific commands and parameters rather than pseudocode.

3 / 3

Workflow Clarity

The 'When Uncertain' section offers a 3-step process and the async section gives clear guidance, but create/delete/cluster operations lack explicit validation checkpoints or error-recovery feedback loops, matching the 'steps listed but validation gaps' anchor.

2 / 3

Progressive Disclosure

No bundle files exist and the entire API reference is inline in SKILL.md with well-organized sections but no one-level-deep pointers to separate reference files, matching the '[200 lines of API reference that could be in a separate file]' anchor.

2 / 3

Total

9

/

12

Passed

Description

90%

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 description with explicit 'Use when' triggers, good natural trigger terms, and a clear Databricks niche. Its only weakness is that it enumerates tools/capabilities rather than concrete actions.

Suggestions

Add concrete actions to the capability list (e.g., 'create clusters, run jobs, manage Unity Catalog tables, deploy model serving endpoints') to lift specificity from listing tools to listing verbs.

DimensionReasoningScore

Specificity

The description names the domain and concrete components ('Python SDK, Databricks Connect, CLI, and REST API') but does not list concrete actions (no verbs like 'create clusters' or 'run jobs'), matching the 'names domain and some actions, but not comprehensive' anchor rather than the multiple-specific-actions level 3.

2 / 3

Completeness

It explicitly answers both what ('Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API') and when ('Use when working with databricks-sdk, databricks-connect, or Databricks APIs') with an explicit trigger clause.

3 / 3

Trigger Term Quality

The 'Use when working with databricks-sdk, databricks-connect, or Databricks APIs' clause covers the natural package names and API phrasing a developer would actually say, with good variation coverage.

3 / 3

Distinctiveness Conflict Risk

The Databricks-specific tooling niche (SDK, Connect, CLI, REST API) with package-name triggers is clearly distinguishable and unlikely to fire for unrelated skills.

3 / 3

Total

11

/

12

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.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (626 lines); consider splitting into references/ and linking

Warning

relative_links

Relative link issues: 7 suspicious

Warning

Total

14

/

16

Passed

Repository
databricks-solutions/ai-dev-kit
Reviewed

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