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First fixture skill for skdd add tests. Use when testing drop installation.
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Basierend auf der SOC-Berufsklassifikation
Close implementation loops with target-bound independent evidence and a portable proof receipt. Use when an agent changes a real system and must earn a completion claim that survives the session.
Second fixture skill for skdd add tests. Use when testing multi-skill drops.
Safely backfill historical data for a pipeline stage — scope the date range, run a dry-run, execute in chunks to avoid overwhelming the database, and verify row counts after each chunk. Use when historical data is missing, when a pipeline stage is added retroactively, or when asked to "backfill the {stage} table from {start_date}".
Add or extend data validation checks in the pipeline when data quality issues are detected — null-percentage thresholds, value ranges, referential integrity, and row-count sanity checks. Use when a pipeline breaks on bad data, when onboarding a new dataset, or when asked to "add a quality check for {column}".
Onboard a new raw dataset into the data platform — sniff the schema, generate a profiling notebook, create the ingestion job, and add an entry to the data dictionary. Use when adding a new data source, when a partner delivers a new CSV/Parquet drop, or when asked to "onboard the {name} dataset".
Record a model training run — log parameters, metrics, and artifact paths, then append a structured row to the experiments ledger. Use when a training run completes, when asked to "log this experiment", or when comparing runs to decide which model to promote.
| name | alpha-skill |
| description | First fixture skill for skdd add tests. Use when testing drop installation. |
| metadata | {"pack":"2026-01-test","forged-by":"fixture-bot","forged-from":"fixture-session","forged-reason":"exists to be installed by tests","usage-count":"0"} |
