Loading...
Loading...
Found 130 Skills
MCP architecture patterns, security, and memory management. Auto-loads when building MCP servers, implementing tools/resources, discussing MCP security, or working with FastMCP.
Guide for debugging and fixing bugs in the OCaml garbage collector, particularly memory management issues in the runtime's sweeping and allocation code. This skill applies when working on OCaml runtime C code, investigating segfaults in GC operations, or fixing pointer arithmetic bugs in memory managers with size-classed pools and run-length encoding.
Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM w...
Identificación de cuellos de botella: CPU, memoria, event loop, queries lentas, Core Web Vitals.
Log a workflow mistake, fix its root cause, and graduate the lesson to learned memory. Use when the agent makes an error you want to prevent recurring.
Use when the user needs conversation continuity, memo, or restore-after-restart behavior for a request family, including session ids, chat history, request-side memory boundaries, and session-backed continuity.
This skill should be used when the user asks to "use NumPy", "write NumPy code", "optimize NumPy arrays", "vectorize with NumPy", or needs guidance on NumPy best practices, array operations, broadcasting, memory management, or scientific computing with Python.
Measure Jetson DRAM/NvMap usage and verify before/after memory reclamation with live audit data.
Master iOS development foundations - Architecture, lifecycle, memory, concurrency
This skill provides Zig memory management guidance. It ensures proper use of defer/errdefer patterns, allocators, and leak detection. Essential for writing Zig code with dynamic allocation, fixing memory leaks, implementing resource cleanup, and working with allocators.
OpenViking long-term memory plugin guide. Once installed, the plugin automatically remembers important facts from conversations and recalls relevant context before responding.
Optimize MATLAB code for better performance through vectorization, memory management, and profiling. Use when user requests optimization, mentions slow code, performance issues, speed improvements, or asks to make code faster or more efficient.