Extract patterns and generalizations from multiple observations. Use when detecting recurring themes, building predictive rules, or identifying systemic behaviors from accumulated data. Produces validated patterns with confidence bounds and exception handling.
Expert in building Datalog queries for Logseq DB graphs. Auto-invokes when users need help writing Logseq queries, understanding Datalog syntax, optimizing query performance, or working with the Datascript query engine. Covers advanced query patterns, pull syntax, aggregations, and DB-specific query techniques.
Visualize datasets in 2D using embeddings with UMAP or t-SNE dimensionality reduction. Use when users want to explore dataset structure, find clusters in images, identify outliers, color samples by class or metadata, or understand data distribution. Requires FiftyOne MCP server with @voxel51/brain plugin installed.
Interactive database query builder for generating optimized SQL and NoSQL queries.
Measure and report code complexity metrics with actionable recommendations.
Use when ready to document findings, generate a report, or summarize binary analysis results. Compiles analysis findings into structured reports - correlates facts from triage/static/dynamic phases, validates hypotheses, generates documentation with evidence chains. Keywords - "summarize findings", "generate report", "document analysis", "what did we find", "write up results", "export findings"
Execute evidence-based decision-making through 6-stage causal flow. Use for known processes, operational execution, and decisions with clear cause-effect chains.
Parse, transform, and analyze CSV files with advanced data manipulation capabilities.
Expert SQL query writing, optimization, and database schema design with support for PostgreSQL, MySQL, SQLite, and SQL Server. Use when working with databases for: (1) Writing complex SQL queries with joins, subqueries, and window functions, (2) Optimizing slow queries and analyzing execution plans, (3) Designing database schemas with proper normalization, (4) Creating indexes and improving query performance, (5) Writing migrations and handling schema changes, (6) Debugging SQL errors and query issues
Generate comprehensive network infrastructure reports including health status, performance analysis, security audits, and capacity planning recommendations.
Create interactive Desmos graphs in Obsidian using desmos-graph code blocks. Use when visualizing functions, parametric curves, inequalities, or mathematical relationships with customizable styling and settings.
Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.
Detect and report drift between database schema and code data models. Works with SQLAlchemy, Django ORM, Prisma, TypeORM, and other ORMs. Generic across any project.
High-performance PostgreSQL patterns. Use when optimizing queries, designing for scale, or debugging performance issues.
Generate database schema diagrams, ERDs, and documentation from database schemas.
Write secure, performant, and optimized database queries using parameterized queries, eager loading, proper indexing, and transaction management. Use this skill when writing database queries in controllers, repositories, services, or model methods, when using query builders or ORM methods, when implementing filtering/sorting/pagination logic, when optimizing N+1 query problems with eager loading, when working with joins and complex queries, when implementing query caching, or when wrapping related operations in database transactions.
SQL query optimization and database performance specialist. Use when optimizing slow queries, fixing N+1 problems, designing indexes, implementing caching, or improving database performance. Works with PostgreSQL, MySQL, and other databases.
Manage database schemas, Drizzle ORM, migrations, and data modeling. Use when creating tables, modifying columns, or planning database changes.
PostgreSQL patterns for reviewing migrations and writing efficient queries. Use when reviewing Alembic migrations, optimizing queries, or debugging database issues.
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
