datajunction-semantic-model

datajunction-semantic-model is a Data warehousing & modelling skill for AI agents, published by DataJunction in the dj repository on GitHub. Skillspace rates datajunction-semantic-model D (57/100) and it passed the safety scan; the rating is based on static analysis only.

Activate this skill for DataJunction (DJ) semantic modeling decisions — choosing the right node shape (fact, dimension, transform, metric, cube), turning a draft SQL query into well-designed nodes, and the cross-cutting conventions (ownership, naming, namespace organization). Format-agnostic modeling guidance; for YAML schemas and the repo-backed authoring flow, invoke `datajunction-repo`; for direct API examples, invoke `datajunction-api`. For DJ concepts (node types, dim links), invoke `datajunction`. For querying existing metrics, invoke `datajunction-query`. Keywords: - semantic modeling - decompose query, model query, query to nodes - create metric, create dimension, create node, create cube, build cube - ratio metric, derived metric, base metric - composable metrics - metric query constraints - node ownership, metric ownership - metric naming, namespace organization - grain, fact vs dimension - dimension link, not JOIN

Grade

D

Quality

57 / 100

Safety

Passed

GitHub stars

155

Unproven: rated by static analysis only, not yet compared head-to-head.

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