System and library dependency mapping, vulnerability scanning, upgrade risk assessment, and license compliance analysis. Use when the user asks to "map dependencies", "analyze dependency risk", "check license compliance", "assess upgrade risk", or mentions dependency graph, vulnerability scanning, or supply chain security.

Use when the user asks to "define Definition of Done", "set acceptance criteria", "establish DoD/DoR standards", "define quality standards", or "create completion checklists". Activates when a stakeholder needs to establish Definition of Done criteria at story/feature/release levels, create Definition of Ready checklists, design acceptance criteria templates, define exception handling processes, or plan DoD evolution protocols.

Use when the user asks to "define Definition of Done", "set acceptance criteria", "establish DoD/DoR standards", "define quality standards", or "create completion checklists". Activates when a stakeholder needs to establish Definition of Done criteria at story/feature/release levels, create Definition of Ready checklists, design acceptance criteria templates, define exception handling processes, or plan DoD evolution protocols.

Database design — schema patterns, indexing, partitioning, replication, migration, performance tuning. Use when the user asks to "design the database schema", "plan indexing strategy", "set up replication", "partition large tables", "migrate database schema", "tune query performance", or mentions normalization, sharding, B-tree indexes, zero-downtime migration, or connection pooling.

Database design — schema patterns, indexing, partitioning, replication, migration, performance tuning. Use when the user asks to "design the database schema", "plan indexing strategy", "set up replication", "partition large tables", "migrate database schema", "tune query performance", or mentions normalization, sharding, B-tree indexes, zero-downtime migration, or connection pooling.

Visual data narrative design — chart selection, Mermaid diagram metodologia-storytelling, visual hierarchy, dashboard narratives, and annotation strategy. Use when selecting chart types, designing diagram narratives, building visual sequences for presentations, or annotating data visualizations for maximum comprehension.

Visual data narrative design — chart selection, Mermaid diagram metodologia-storytelling, visual hierarchy, dashboard narratives, and annotation strategy. Use when selecting chart types, designing diagram narratives, building visual sequences for presentations, or annotating data visualizations for maximum comprehension.

Transforms metrics and findings into meaningful narratives — insight extraction, metrics-to-meaning conversion, comparison framing, and magnitude communication. Use when presenting scoring matrices, coverage metrics, performance data, cost estimates, or any quantitative finding that needs interpretation and context.

Transforms metrics and findings into meaningful narratives — insight extraction, metrics-to-meaning conversion, comparison framing, and magnitude communication. Use when presenting scoring matrices, coverage metrics, performance data, cost estimates, or any quantitative finding that needs interpretation and context.

ML/AI system design — model lifecycle, feature stores, experiment tracking, model serving, MLOps pipelines. Use when the user asks to "design an ML system", "architect model serving", "set up experiment tracking", "design feature store", "plan MLOps pipeline", or mentions model registry, A/B testing, drift detection, or retraining triggers.

ML/AI system design — model lifecycle, feature stores, experiment tracking, model serving, MLOps pipelines. Use when the user asks to "design an ML system", "architect model serving", "set up experiment tracking", "design feature store", "plan MLOps pipeline", or mentions model registry, A/B testing, drift detection, or retraining triggers.

Data quality framework — profiling, validation, anomaly detection, data contracts, SLA monitoring. Use when the user asks to "design data quality framework", "set up data contracts", "plan data validation", "detect data anomalies", "define data SLAs", or mentions data profiling, quarantine patterns, or remediation workflows.

Data quality framework — profiling, validation, anomaly detection, data contracts, SLA monitoring. Use when the user asks to "design data quality framework", "set up data contracts", "plan data validation", "detect data anomalies", "define data SLAs", or mentions data profiling, quarantine patterns, or remediation workflows.

Data mesh readiness assessment and strategy using Zhamak Dehghani's 4 principles. Use when the user asks to "assess data mesh readiness", "design data mesh strategy", "domain data ownership", "data as a product", "self-serve data platform", "federated data governance", "data mesh migration", or mentions "data decentralization", "data domain ownership", "data product thinking".

Data mesh readiness assessment and strategy using Zhamak Dehghani's 4 principles. Use when the user asks to "assess data mesh readiness", "design data mesh strategy", "domain data ownership", "data as a product", "self-serve data platform", "federated data governance", "data mesh migration", or mentions "data decentralization", "data domain ownership", "data product thinking".

Data governance framework — catalog, ownership, classification, retention, privacy compliance, data mesh. Use when the user asks to "build a data catalog", "define data ownership", "classify sensitive data", "design retention policies", "ensure privacy compliance", "implement data mesh governance", or mentions GDPR, CCPA, LGPD, data stewardship, PII, data lineage, or federated governance.

Data governance framework — catalog, ownership, classification, retention, privacy compliance, data mesh. Use when the user asks to "build a data catalog", "define data ownership", "classify sensitive data", "design retention policies", "ensure privacy compliance", "implement data mesh governance", or mentions GDPR, CCPA, LGPD, data stewardship, PII, data lineage, or federated governance.

Data pipeline architecture — ingestion, orchestration, quality, lineage, SLAs. Use when the user asks to "design data pipelines", "architect ingestion", "set up orchestration", "plan data lake", "design lakehouse", or mentions Airflow, Dagster, CDC, data lineage, or pipeline SLAs.

Data pipeline architecture — ingestion, orchestration, quality, lineage, SLAs. Use when the user asks to "design data pipelines", "architect ingestion", "set up orchestration", "plan data lake", "design lakehouse", or mentions Airflow, Dagster, CDC, data lineage, or pipeline SLAs.

Use when the user asks to "configure dashboards", "set up data feeds", "design monitoring tools", "automate dashboard updates", or "integrate PM data sources". Activates when a stakeholder needs to configure PM dashboard tooling, set up automated data feeds from PM tools, design visualization components, configure alert thresholds, or establish dashboard refresh cadence and access control.