databricks-multi-env-setup

Configure Databricks across development, staging, and production environments. Use when setting up multi-environment deployments, configuring per-environment secrets, or implementing environment-specific Databricks configurations. Trigger with phrases like "databricks environments", "databricks staging", "databricks dev prod", "databricks environment setup", "databricks config by env".

Quality

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Quality

Content

65%

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

The skill body is highly actionable with executable examples but is monolithic — full configuration files are inlined rather than split into reference files, and validation checkpoints are not embedded in the deploy/secret workflows. Tightening disclosure and adding inline verification steps would raise the lower dimensions.

Suggestions

Move the full databricks.yml, GitHub workflow, and Terraform blocks into reference files (e.g. references/bundle.yml, references/ci-deploy.yml, references/terraform.tf) and link to them from SKILL.md to improve progressive disclosure and conciseness.

Add explicit validation checkpoints inside the workflow steps — e.g. after Step 3 verify scopes with `databricks secrets list-scopes --profile $env` before proceeding, and after Step 5 run the Quick Environment Verification before promoting to prod — rather than relegating verification to a separate Examples section.

Embed a verify-after-deploy step in the production deploy job (Step 5) so the destructive/batch production deployment has a feedback loop, which would lift workflow_clarity above 2.

Dimension	Reasoning	Score
Conciseness	The body is accurate and mostly executable, but it dumps several full configuration files inline (databricks.yml, Python dataclass, GitHub workflow, Terraform) plus a deprecation block, which is more tokens than a tightened version would need.	2 / 3
Actionability	Every step ships complete, copy-paste-ready code/commands — ini profiles, bundle YAML, secret-scope bash loop, Python config, CI workflow, Terraform — with specific flags and values rather than pseudocode.	3 / 3
Workflow Clarity	Steps 1–6 are clearly sequenced, but the batch secret-scope loop and production `databricks bundle deploy -t prod` lack validation checkpoints woven into the workflow; verification appears only in a separate Examples section, capping clarity at 2.	2 / 3
Progressive Disclosure	Sections are well-organized, but there are no bundle files at all and large config/CI/Terraform blocks that belong in separate reference files are inline, fitting the 'content that should be separate is inline' anchor.	2 / 3
	Total	9 / 12 Passed

Description

100%

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 third-person, concise, and explicitly states both capabilities and trigger conditions with natural keywords. It is a strong, complete description that satisfies every dimension.

Dimension	Reasoning	Score
Specificity	Names the domain and multiple concrete actions — 'Configure Databricks across development, staging, and production environments', 'setting up multi-environment deployments, configuring per-environment secrets' — matching the multiple-specific-actions anchor.	3 / 3
Completeness	Clearly answers both what (configure Databricks across environments / per-env secrets) and when via an explicit 'Use when...' clause plus a 'Trigger with phrases like...' list.	3 / 3
Trigger Term Quality	Explicit natural trigger phrases a user would say — 'databricks environments', 'databricks staging', 'databricks dev prod', 'databricks environment setup' — giving good coverage of common variations.	3 / 3
Distinctiveness Conflict Risk	The Databricks multi-environment setup niche with environment-specific trigger phrases is clearly distinguishable and unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

87%

Warnings & errors only

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

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Commit: 02d6341

Reviewed: about 15 hours ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.