performance
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distributed-tracing
Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.
debugging-orm-queries
Converts ORM calls to raw SQL and analyzes query performance. Detects N+1 queries, missing indexes, and other anti-patterns. Use when debugging slow queries, tracing ORM-generated SQL, or optimizing database performance for Sequelize, Prisma, TypeORM (Node.js), GORM, sqlc, sqlx, ent (Go), or SQLAlchemy, Django ORM, Peewee (Python).
dspy-miprov2-optimizer
State-of-the-art Bayesian optimization for DSPy programs with joint instruction and demo tuning
memory-management-optimization
Debug memory leaks, profile memory usage, optimize allocations. Use when heap grows unexpectedly, OOM errors occur, or profiling shows memory bottleneck. Covers C++ (Valgrind, ASAN, RAII), Python (tracemalloc, objgraph), and general patterns.
asset-optimization
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optimization-performance
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routing-performance-implementation
Configure routing with lazy loading, implement route guards, set up preloading strategies, optimize change detection, analyze bundles, and implement performance optimizations.
Python Backend Architecture Review
Comprehensive design architecture review for Python backend applications. Use this skill when users ask you to review, analyze, or provide feedback on backend architecture designs, system design documents, or Python application architecture. Covers scalability, security, performance, database design, API design, microservices patterns, deployment architecture, and best practices.
async-programming
Concurrent operations with asyncio and Tokio, focusing on race condition prevention, resource safety, and performance
rust
Systems programming expertise for Tauri desktop application backend development with memory safety and performance optimization
llm-integration
Expert skill for integrating local Large Language Models using llama.cpp and Ollama. Covers secure model loading, inference optimization, prompt handling, and protection against LLM-specific vulnerabilities including prompt injection, model theft, and denial of service attacks.
model-quantization
Expert skill for AI model quantization and optimization. Covers 4-bit/8-bit quantization, GGUF conversion, memory optimization, and quality-performance tradeoffs for deploying LLMs in resource-constrained JARVIS environments.
wp-performance-review
Use when reviewing WordPress PHP code for performance issues, auditing themes/plugins for scalability, optimizing WP_Query, analyzing caching strategies, or detecting anti-patterns in database queries, hooks, object caching, AJAX, and template loading.
refactoring
Restructures existing code to improve readability, maintainability, and performance without changing external behavior. Trigger keywords: refactor, restructure, clean up, improve code, simplify, extract, modernize.
sql-optimization
Analyzes and optimizes SQL queries for better performance, including index design and query rewriting. Trigger keywords: sql, query optimization, slow query, index, explain, performance, database tuning.
performance-optimization
Performance profiling, optimization techniques, and bottleneck identification. Use when addressing performance issues or optimizing systems.
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