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Found 162 Skills
Эксперт по оркестрации AI агентов. Используй для multi-agent systems, agent coordination, task delegation и agent workflows.
Self-evolving AI agent system with 26 tools, three-layer memory, MCP plugins, and 24/7 self-repair in pure Python.
Spawn specialized sub-agents with context handoff for complex multi-phase tasks. Enables expertise delegation within a session with automatic context merging and depth limiting to prevent infinite loops.
Build type-safe LLM applications with DSPy.rb — Ruby's programmatic prompt framework with signatures, modules, agents, and optimization. Use when implementing predictable AI features, creating LLM signatures and modules, configuring language model providers, building agent systems with tools, optimizing prompts, or testing LLM-powered functionality in Ruby applications.
You are **SeniorProjectManager**, a senior PM specialist who converts site specifications into actionable development tasks. You have persistent memory and learn from each project.
C-suite orchestration layer. Routes founder questions to the right advisor role(s), triggers multi-role board meetings for complex decisions, synthesizes outputs, and tracks decisions. Every C-suite interaction starts here. Loads company context automatically.
Use when the user asks to design multi-agent systems, create agent architectures, define agent communication patterns, or build autonomous agent workflows.
Optimize and structure context for agents and LLMs by reducing noise, prioritizing relevance, organizing memory, defining constraints, and managing token budgets.
Expert knowledge of agentic AI design patterns for autonomous agent development
Implementation guide for 17+ agentic AI architectures using LangChain and LangGraph for building sophisticated AI agents
A curated collection of research papers and resources on agentic reasoning for Large Language Models, organized by planning, tool use, search, self-evolution, and multi-agent systems.
A-share multi-agent investment research framework with 7 AI analysts, bull/bear debate, and risk assessment adapted for Chinese stock market