Skills

Dbt Ingest

Map dbt `schema.yml` / `properties.yml` models and sources into ktx semantic-layer...

Install

npx skills add Kaelio/ktx --skill dbt_ingest -g -a claude-code -y
Repository
Kaelio/ktx1.6k
Category
Git and review
Updated
13d ago
License
Apache-2.0
Context cost
Mediumabout 1,562 tokens
Runs scripts
No, instructions only

What it does

Map dbt `schema.yml` / `properties.yml` models and sources into ktx semantic-layer overlays and column notes. Covers `sources:` vs `models:`, column `data_tests` (not_null, unique, accepted_values, relationships), and how bundle-time writes complement manifest backfill from git sync. Load when the WorkUnit's `skillNames` includes `dbt_ingest` or when raw files are dbt YAML under `models/` / `sources/`.

dbt → ktx (bundle ingest)

Use this skill for uploaded dbt projects (dbt_project.yml at stage root, models/**, sources/**, schema.yml). There is no fetch() in v1 - scheduled dbt parse / manifest.json pulls are out of scope; host-provided dbt sync may still backfill structured test metadata into _schema on the next sync.

Mapping (models / sources → SL)

dbtktxNotes
models: entry with columns:Overlay on the manifest table with the same name (after discover_data / entity_details)One SL source per physical table; model name may differ from DB name - resolve with read_raw_file + warehouse context.
sources: → tables:Same as models; use identifier when present instead of logical name.Schema + name must match how the connection sees tables.
Column descriptioncolumn_overrides[].descriptions.user on the overlayDo not overwrite dbt description keys from sync.
data_tests: not_null / uniqueShort hint in column descriptions or notes: “dbt: not null”, “dbt: unique”Full structured metadata lands in manifest via sync; the skill keeps bundle-time SL text useful for the agent.
accepted_valuesAdd a brief line in the column description: allowed values (truncate long lists)Also mention enum-like use in discover_data / filters.
relationshipsAdd or confirm joins: on the overlay only when to resolves to a real table via read_raw_file + discover_data / entity_detailsIf the ref cannot be resolved, capture the intent in a wiki page instead.

Physical schema grounding

Read the whole SKILL.md on GitHub

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