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Found 84 Skills
Reviews Elixir code for performance issues including GenServer bottlenecks, memory usage, and concurrency patterns. Use when reviewing high-throughput code or investigating performance issues.
Execute tasks from TODO file - Generic task runner [/todo-task-run xxx]
Identificación de cuellos de botella: CPU, memoria, event loop, queries lentas, Core Web Vitals.
Save current session state to Apple Notes at session end. Triggers on handoff, bye, done, wrap up, or Chinese equivalents. Multi-agent architecture with private (per-agent) and shared (cross-agent) notes. Three-tier memory: Active, Archive, Long-term. Use whenever the user wants to end a session, save progress, or says anything indicating they are done for now.
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.
Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.
Guide for writing MoonBit bindings to C libraries using native FFI. Use when adding extern "c" declarations, writing C stubs with moonbit.h, configuring native-stub and link.native in moon.pkg, choosing
Provides Zig patterns for type-first development with tagged unions, explicit error sets, comptime validation, and memory management. Must use when reading or writing Zig files.
Letta framework for building stateful AI agents with long-term memory. Use for AI agent development, memory management, tool integration, and multi-agent systems.
AI Agent long-term memory system with cross-session, cross-project persistence. Triggers: - /remember - Store memories - /recall - Search memories - /forget - Delete/archive memories - /memory-status - Check status - When needing to persist important conversation insights - When sharing user preferences across projects
Comprehensive guidelines for Obsidian.md plugin development including all 27 ESLint rules, TypeScript best practices, memory management, API usage (requestUrl vs fetch), UI/UX standards, and submission requirements. Use when working with Obsidian plugins, main.ts files, manifest.json, Plugin class, MarkdownView, TFile, vault operations, or any Obsidian API development.
Apply systematic performance optimization techniques when writing or reviewing code. Use when optimizing hot paths, reducing latency, improving throughput, fixing performance regressions, or when the user mentions performance, optimization, speed, latency, throughput, profiling, or benchmarking.