Activate this skill whenever working with DataJunction (DJ) semantic layer. Core concepts and shared vocabulary used by every DJ workflow. For querying metrics, invoke datajunction-query. For modeling decisions (what shape something should take), invoke datajunction-semantic-model. For authoring nodes, invoke datajunction-repo (YAML in a git repo) or datajunction-api (REST API for exploration / prototyping).
EnglishActivate this skill when authoring DataJunction (DJ) nodes via the REST API directly (curl, HTTP clients) — typically for exploration, ad-hoc prototyping, or namespaces that aren't repo-backed. For modeling decisions and the decomposition workflow, invoke datajunction-semantic-model. For repo-backed YAML authoring (the production path), invoke datajunction-repo. For concepts, invoke datajunction.
EnglishActivate this skill for querying DataJunction (DJ) — finding nodes, generating SQL, fetching metric data, exploring lineage, visualizing results — via the DJ UI, MCP tools, or REST/GraphQL APIs. For core DJ concepts and vocabulary, invoke datajunction. For modeling decisions (what shape something should take), invoke datajunction-semantic-model. For authoring nodes, invoke datajunction-repo (YAML) or datajunction-api (REST).
EnglishActivate this skill when authoring DataJunction (DJ) nodes via YAML files in a git repository — the repo-backed workflow. Covers YAML schemas per node type, branch-based development, temporal partitions on cubes, and the full PR-driven deployment flow. For modeling decisions (how to structure metrics, decomposition workflow), invoke datajunction-semantic-model. For direct API authoring, invoke datajunction-api. For concepts, invoke datajunction.
EnglishActivate 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.
English
AGENT SKILLS ATLASIncludes Datajunction, Datajunction API, Datajunction Query, and other workflows.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLISupported by the Atlas install prompt. Skill-specific requirements vary.
Pack stats
What’s included
Datajunction
Activate this skill whenever working with DataJunction (DJ) semantic layer. Core concepts and shared vocabulary used by every DJ workflow. For querying metrics, invoke datajunction-query. For modeling decisions (what shape something should take), invoke datajunction-semantic-model. For authoring nodes, invoke datajunction-repo (YAML in a git repo) or datajunction-api (REST API for exploration / prototyping). Keywords: - DataJunction, DJ - semantic layer - dimension link, dimension links - star schema - node types - source, transform, dimension, metric, cube - metric, metrics - mode, status, valid, invalid, draft, published - namespace
Datajunction API
Activate this skill when authoring DataJunction (DJ) nodes via the REST API directly (curl, HTTP clients) — typically for exploration, ad-hoc prototyping, or namespaces that aren't repo-backed. For modeling decisions and the decomposition workflow, invoke datajunction-semantic-model. For repo-backed YAML authoring (the production path), invoke datajunction-repo. For concepts, invoke datajunction. Keywords: - DJ API, REST API, curl - POST nodes/metric, POST nodes/dimension - create metric, create dimension, create cube - API approach, direct API changes - prototyping, exploration
Datajunction Query
Activate this skill for querying DataJunction (DJ) — finding nodes, generating SQL, fetching metric data, exploring lineage, visualizing results — via the DJ UI, MCP tools, or REST/GraphQL APIs. For core DJ concepts and vocabulary, invoke datajunction. For modeling decisions (what shape something should take), invoke datajunction-semantic-model. For authoring nodes, invoke datajunction-repo (YAML) or datajunction-api (REST). Keywords: - query metric, query metrics - generate SQL, build metric SQL - get metric data, fetch metric - available dimensions, common dimensions - searchnodes, getnodedetails, getnodelineage - getcommon, buildmetricsql, getmetricdata - visualize metrics - MCP tools, DJ API, GraphQL - DJ UI, web UI, browse
Datajunction Repo
Activate this skill when authoring DataJunction (DJ) nodes via YAML files in a git repository — the repo-backed workflow. Covers YAML schemas per node type, branch-based development, temporal partitions on cubes, and the full PR-driven deployment flow. For modeling decisions (how to structure metrics, decomposition workflow), invoke datajunction-semantic-model. For direct API authoring, invoke datajunction-api. For concepts, invoke datajunction. Keywords: - YAML nodes, YAML definitions - repo-backed namespace, repo-backed workflow - git workflow, branch development, feature branch - cube YAML, metric YAML, dimension YAML, transform YAML - create metric, create dimension, create cube, build cube - temporal partition, partition pushdown - pre-commit, push.sh
Datajunction Semantic Model
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
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Use the Datajunction skill to help with my task.
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