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Use when designing data architectures, building batch or streaming pipelines, implementing data quality frameworks, optimizing ETL/ELT performance, working with Airflow/dbt/Spark/Kafka, or troubleshooting data pipeline failures. Provides pipeline generation, data quality validation, and SQL/Spark performance optimization.

This skill should be used when the user asks to "optimize Snowflake queries", "analyze Snowflake SQL performance", "size Snowflake warehouses", "review Snowflake data models", or "troubleshoot Snowflake cost issues".

Expert people analytics covering workforce analytics, HR metrics, predictive modeling, employee insights, and data-driven HR decisions. Use when building turnover prediction models, analyzing engagement surveys, running pay equity regressions, designing people dashboards, scoring flight risk, or advising HR leaders with workforce data.

Design a product metrics dashboard — North Star + input metrics + guardrails — that the team actually uses to make decisions. Distinct from north-star-metric (defines THE one number) by focusing on the full dashboard architecture: layers, owners, cadence, visualization, and the discipline that prevents 30-chart dashboards.

Product analytics framework for PMs and analytics engineers on instrumenting products, defining metrics, building activation/retention funnels, running cohort analyses, and translating product data into decisions. Use when designing a product metric tree, instrumenting a new feature, auditing existing instrumentation, defining North Star + counter-metrics, or building an analytics roadmap.

Data-driven sprint retrospectives with velocity analytics, contributor insights, code quality trends, and actionable improvement recommendations. Analyzes git history to produce comprehensive retrospective reports with session detection, churn hotspots, work pattern analysis, and sprint-over-sprint comparison dashboards.

Expert sales operations covering CRM management, sales analytics, territory planning, compensation design, and process optimization. Use when building pipeline reports, designing territories, setting quotas, creating comp plans, or auditing CRM data quality.

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

Amazon Brand Analytics interpretation and strategic insights for Brand Registry owners. Decode Search Frequency Rank (SFR) data, analyze Market Basket patterns, interpret Item Comparison reports, and extract demographic insights to optimize product strategy and advertising spend. Works with Brand Analytics data from all Amazon marketplaces. Requires Brand Registry access. Use when: (1) analyzing S

Analyze competitor pricing strategies across e-commerce platforms. Map price positions, identify pricing gaps, evaluate price elasticity signals, and develop data-driven pricing strategies.