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Validates dimensional models against Kimball methodology best practices
Passed 19 of 22 test cases with the skill, and 6 of 22 without it.
and 12 more in the full report
13 fixed6 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
We want to track student class attendance, where each record marks a student present in a class on a date, with no numeric facts/measures. Model: {"facts": [{"name": "fact_attendance", "attributes": ["student_key", "class_key", "date_key"]}], "dimensions": ["dim_student", "dim_class", "dim_date"], "relationships": []} for 'Class Attendance'. Return validation JSON.
| Checked | Without skill | With skill |
|---|---|---|
| The response is a JSON object containing top-level key validationScore. | Missed | Passed |
| The JSON response identifies fact_attendance as a factless fact table. | Missed | Passed |
The instructions your model reads when the skill loads.
Validates dimensional models against Kimball methodology best practices. This skill ensures dimensional models conform to proven design patterns for analytical workloads.
{
"model": {
"facts": ["object"],
"dimensions": ["object"],
"relationships": ["object"]
},
"businessProcess": "string",
"busMatrix": "object"
}
{
"validationScore": "number",
"issues": [{
"severity": "error|warning|info",
"element": "string",
test cases passed, vs 6 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.