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Develop AI-powered applications using Genkit in Python. Use when the user asks about Genkit, AI agents, flows, or tools in Python, or when encountering Genkit errors, import issues, or API problems.

Generate database schema diagrams, ERDs, and documentation from database schemas.

Domain knowledge for Physical AI, ROS 2, and Humanoid Robotics.

Systematic architectural thinking that emphasizes irreplaceable human capabilities. Use when designing system architecture, making technology decisions, navigating constraints, or decomposing problems for AI execution. Covers domain modeling, systems thinking, constraint navigation, and AI-aware decomposition.

Species abundance estimation using Bracken with Kraken2 output. Redistributes reads from higher taxonomic levels to species for more accurate estimates. Use when accurate species-level abundances are needed from Kraken2 classification output.

Guides users on creating mock implementations for testing with traits, providing test doubles, and avoiding tight coupling to test infrastructure. Activates when users need to test code with external dependencies.

This skill should be used when evaluating the quality of book chapters, lessons, or educational content. It provides a systematic 6-category rubric with weighted scoring (Technical Accuracy 30%, Pedagogical Effectiveness 25%, Writing Quality 20%, Structure & Organization 15%, AI-First Teaching 10%, Constitution Compliance Pass/Fail) and multi-tier assessment (Excellent/Good/Needs Work/Insufficient

Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants. Use when defining API request/response schemas, database models, or data validation in Python applications using Pydantic v2.

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.

Pack entire codebases into AI-friendly files for LLM analysis. Use when consolidating code for AI review, generating codebase summaries, or preparing context for ChatGPT, Claude, or other AI tools.

Access COSMIC cancer mutation database. Query somatic mutations, Cancer Gene Census, mutational signatures, gene fusions, for cancer research and precision oncology. Requires authentication.