.agents/starflow/skills/starflow-lineage-review/SKILL.md
Review and document data lineage across pipeline stages. Use when the user says "review lineage" or "trace data flow".
npx skillsauth add starlake-ai/starlake-skills starflow-lineage-reviewInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Traces and documents data lineage across all pipeline stages — from source extraction through loading, transformation, and final consumption. Uses Starlake's built-in lineage capabilities and supplements with manual analysis where needed.
Role Guidance: Act as a Data Quality Engineer reviewing data lineage for completeness and correctness.
Trace the flow of data between tables:
starlake lineage --task {domain}.{task} to generate lineage graphsstarlake table-dependencies to list all dependenciesTrace individual columns through transformations:
starlake col-lineage --task {domain}.{task} --column {col} for column tracingTrace access control through the pipeline:
starlake acl-dependencies to map permission flows# Generate table lineage for a task
starlake lineage --task {domain}.{task}
# Trace column lineage
starlake col-lineage --task {domain}.{task} --column {column_name}
# List all table dependencies
starlake table-dependencies
# List ACL dependencies
starlake acl-dependencies
Lineage documentation including:
lineage skill for detailed starlake lineage command optionscol-lineage skill for column-level lineage tracingtable-dependencies skill for dependency graph generationacl-dependencies skill for permission lineageComplete data lineage documentation ensuring traceability from source to consumption for governance, debugging, and impact analysis.
development
Design SQL transformations for data pipelines with quality checks and dependency management. Use when the user says "design transforms" or "create SQL transformations".
devops
Plan and track sprint progress for data pipeline implementation. Use when the user says "sprint planning" or "plan data sprint".
testing
Analyze data sources in depth: schema, quality, volume, and extraction strategy. Use when the user says "analyze data source" or "profile this data source".
data-ai
Design Starlake-compatible table schemas with types, constraints, privacy, and expectations. Use when the user says "design schema" or "create table definition".