Individual skill
troubleshooting-datavault4dbt
Diagnoses common datavault4dbt failures — satellites capturing too many or too few rows, multi-source high-water-mark issues, ghost-record/datatype errors, and YAML-metadata compile errors. Use when a datavault4dbt model errors on compile or run, a satellite detects the wrong number of changes, or a hub/link/satellite loads nothing or duplicates.
skills/datavault4dbt/skills/troubleshooting-datavault4dbt/SKILL.md
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- Last checked
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- License
- Apache-2.0
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- agent-skill Repository topic
- agent-skills Repository topic
- agentic-ai Repository topic
- claude Repository topic
- claude-code Repository topic
- claude-skills Repository topic
- data-vault Repository topic
- data-vault-2 Repository topic
- data-vault-automation Repository topic
- datavault4dbt Repository topic
- engineering Derived category
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# Troubleshooting datavault4dbt
Diagnose datavault4dbt models by symptom. The package generates the SQL, so most issues trace back to
the **staging metadata** (hashkeys/hashdiffs), the **YAML parameters**, or **incremental/HWM** behavior.
## First moves
1. `dbt compile --select <model>` and read the generated SQL in `target/` — it shows exactly what the
macro produced.
2. Enable verbose package logs: set `datavault4dbt.show_debug_logs: true` in `vars:` and re-run, then
read the dbt `.log` file.
3. Inspect the staging output (`dbt show --select <stage_model> --limit 20`) — most raw-vault problems
originate one layer up, in staging.
