dbt
dbt (data build tool) patterns for data transformation and analytics engineering. Use when building data models, implementing data quality tests, or managing data transformation pipelines.
81
77%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/devops-data/skills/dbt/SKILL.mdQuality
Discovery
75%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a solid description that clearly identifies its domain (dbt) and provides explicit 'Use when' guidance, making it easy for Claude to know when to select this skill. However, it could be strengthened with more specific concrete actions and additional trigger terms that users commonly associate with dbt workflows.
Suggestions
Add more specific concrete actions like 'write incremental models', 'configure sources and seeds', 'create reusable macros', or 'set up model dependencies'
Include additional natural trigger terms users might say: 'SQL models', 'staging/marts', 'ref() function', 'dbt run', 'dbt test', '.yml schema files'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (dbt/data transformation) and mentions some actions ('building data models', 'implementing data quality tests', 'managing data transformation pipelines'), but doesn't list specific concrete actions like 'write incremental models', 'configure sources', or 'create macros'. | 2 / 3 |
Completeness | Clearly answers both what ('dbt patterns for data transformation and analytics engineering') and when ('Use when building data models, implementing data quality tests, or managing data transformation pipelines') with explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Includes relevant terms like 'dbt', 'data build tool', 'data models', 'data quality tests', 'data transformation pipelines', but misses common variations users might say like 'SQL models', 'ref()', 'staging models', 'marts', '.yml files', or 'dbt run/test'. | 2 / 3 |
Distinctiveness Conflict Risk | The explicit mention of 'dbt (data build tool)' creates a clear niche that distinguishes it from general SQL skills or other data tools. The specific terminology around analytics engineering and dbt patterns makes conflicts unlikely. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
79%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, concise dbt skill that provides executable patterns for common use cases. Its strengths are token efficiency and actionable code examples. Weaknesses include lack of explicit workflow sequencing for the model development lifecycle and missing references for advanced topics like macros and snapshots.
Suggestions
Add an explicit workflow section showing the sequence: develop model → run dbt run → validate with dbt test → check results before promoting
Include references or brief examples for macros and snapshots since they appear in the project structure but have no guidance
Add a validation checkpoint pattern showing how to verify model outputs (e.g., dbt test, dbt build --select model+)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is lean and efficient, providing only essential patterns without explaining what dbt is or how SQL works. Every section delivers actionable content without padding. | 3 / 3 |
Actionability | Provides fully executable SQL examples with proper dbt syntax (source(), ref(), config blocks, is_incremental()). The YAML test configuration is copy-paste ready. | 3 / 3 |
Workflow Clarity | The staging → intermediate → marts pattern is mentioned but not explicitly sequenced as a workflow. No validation checkpoints for testing models or verifying transformations before deployment. | 2 / 3 |
Progressive Disclosure | Content is well-organized with clear sections, but seeds, macros, and snapshots directories are shown without explanation or references to detailed documentation. Could benefit from links to advanced topics. | 2 / 3 |
Total | 10 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- jpoutrin/product-forge
- Commit
0ebe7ae
- Reviewed
Table of Contents
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