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Found 154 Skills
Design enterprise-grade agent systems with Microsoft's agent framework patterns: role separation, workflow control, policy boundaries, and observability. Use when users need robust organizational agent workflows, governance, and maintainable multi-agent architecture.
Expert in making multi-agent systems resilient. Specializes in detecting loops, hallucinations, and failures, and implementing self-healing workflows. Use when designing error handling for agent systems, implementing retry strategies, or building resilient AI workflows.
Build multiple AI agents that work together. Use when you need a supervisor agent that delegates to specialists, agent handoff, parallel research agents, support escalation (L1 to L2), content pipeline (writer + editor + fact-checker), or any multi-agent system. Powered by DSPy for optimizable agents and LangGraph for orchestration.
Use when designing multi-agent systems, implementing supervisor patterns, coordinating multiple agents, or asking about "multi-agent", "supervisor pattern", "swarm", "agent handoffs", "orchestration", "parallel agents"
Multi-agent distributed context preservation protocol using cryptographic sharding, gossip propagation, and Byzantine fault tolerance to maintain coherent shared memory across dynamic agent networks.
Operate consensus.tools end-to-end (post jobs, create submissions, cast votes, resolve results) using either a local-first board or a hosted board (depending on how you run it). Hosted boards are optional and coming soon.
Activate orchestrator mode for complex multi-task work using subagents. Use when you need to coordinate multiple independent Task subagents to accomplish work while keeping the main context window clean.
Design and scaffold the code execution pattern for MCP-based agent systems. Use when building agents that interact with many MCP tools, when intermediate data is too large for model context, when you need loops/conditionals across tool calls, or when PII must stay out of the model context. Based on Anthropic's engineering guidance.
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
Build and deploy parallel execution via subagent waves, agent teams, and multi-wave pipelines. Use when the Decomposition Gate identifies 2+ independent actions or when spawning teams. NOT for single-action tasks or non-parallel work.
Эксперт по оркестрации AI агентов. Используй для multi-agent systems, agent coordination, task delegation и agent workflows.
Deep dive into a book. Collect information from six dimensions including chapter structure, background key points, problem impacts, solutions, term index, and further reading through parallel sub-agents, then output a Markdown deep learning note after cross-analysis. Trigger words: Analyze the book XX, Study XX, Reading notes for XX, book analysis.