Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.

Conducts comprehensive code quality reviews including code smells detection, maintainability assessment, complexity analysis, design pattern evaluation, naming conventions, code duplication,...

Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when...

Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit

Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory...

Conducts comprehensive security code reviews including vulnerability detection (OWASP Top 10, CWE), authentication/authorization flaws, injection attacks, cryptography issues, sensitive data...

Analyzes and assists with Fujitsu mainframe systems including FACOM, PRIMERGY, BS2000/OSD, OSIV/MSP, OSIV/XSP, NetCOBOL, PowerCOBOL, and Fujitsu JCL. Extracts business logic from Fujitsu COBOL...

Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization...

Expert frontend development guidance covering React, Vue, Angular, TypeScript, state management, component architecture, performance optimization, accessibility, testing, and modern web APIs....

Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4,...

Jeffrey Emanuel's multi-agent implementation workflow using NTM, Agent Mail, Beads, and BV. The execution phase that follows planning and bead creation. Includes exact prompts used.

Designs comprehensive integration testing strategies including API testing, database testing, microservices testing, end-to-end testing, and test automation frameworks. Produces test plans, test...

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with...

Simplify and refine recently modified code for clarity and consistency. Use after writing code to improve readability without changing functionality.

Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training large MoE models with FP8/INT4, needing train-inference alignment, or requiring...

Iterative UI/UX polishing workflow for web applications. The exact prompt and methodology for achieving Stripe-level visual polish through multiple passes.

Guides comprehensive software project planning including task breakdown, estimation, sprint planning, backlog management, resource allocation, milestone tracking, and risk management. Creates user...

Conducts comprehensive backend code reviews including API design (REST/GraphQL/gRPC), database patterns, authentication/authorization, caching strategies, message queues, microservices...

Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or...

Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2