name: control-namespace-health description: "Report fill-rate and orphan health across the control namespace instance data. Read-only data quality audit. Triggers on: 'control health', 'fill rate', 'orphan nodes', 'data quality', 'control completeness', 'sparse nodes'."
Control Namespace Health
When to Use
- User wants a data-quality overview of control namespace instances
- User asks for fill-rate statistics (which properties are populated)
- User wants to find orphan or sparse nodes in the control graph
- User asks for a health dashboard before a phase-gate review
Workflow
Enumerate control models. List all models in the namespace:
gm_model_list(namespace="control", summary_only=True)Profile each model. Run data profiling per model to get fill-rate statistics:
gm_data_profile(model_ref="alarm-management", namespace="control")Repeat for each control model that has instance data in Neo4j.
Validate instance data. Run instance validation to detect orphans and sparse nodes:
gm_data_validate(model_ref="alarm-management", namespace="control")Aggregate fill rates. Collect per-label, per-property fill percentages across all models. Flag properties below 50% fill as warnings and below 20% as errors.
Render health dashboard. Present findings as a markdown report:
- Summary table: model, label count, relationship count, avg fill %
- Low-fill properties table: model, label, property, fill %
- Orphan/sparse node list with model and label
- Overall health score (% of properties above threshold)
Pitfalls
- This skill is read-only — it reports data quality but does not
fix it. Instance fixes use
gm_cypher(mode="write"); type fixes go through the ontologist. - Low fill rates on stub nodes are expected — stubs intentionally carry fewer properties than their source-of-truth counterparts.
- Models without instance data in Neo4j will return empty profiles — this is not an error, just an indication that the model has not been materialized or populated yet.
Related Skills
control-namespace-audit— complementary type-consistency audit (schema drift, key mismatches).