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SOP for validating that candidate axes are independent and meaningful.
Passed 2 of 14 test cases with the skill, and 2 of 14 without it.
1 fixed3 passed either way19 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
For our FedEx fleet tracking dashboard, we are assessing dimensions: ['speed_mph', 'velocity_kph', 'fuel_level_pct', 'country_jurisdiction']. The fleet operates exclusively in 'USA'. Evaluate all four candidate dimensions for pairwise independence and utility, returning JSON with keys 'validated', 'merged', and 'removed'.
| Checked | Without skill | With skill |
|---|---|---|
| The response conducts pairwise independence tests across all six dimension pairs. | Missed | Passed |
| The response merges speed_mph and velocity_kph. | Passed | Passed |
| The response categorizes country_jurisdiction under removed. | Passed | Passed |
The instructions your model reads when the skill loads.
Verify that candidate dimensions are truly independent and meaningful.
vault_query_graph + vault_search
Returns: { validated: string[], merged: string[], removed: string[] }
test cases passed, vs 2 / 14 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.