Build AI agents using the Azure AI Agents Python SDK (azure-ai-agents). Use when creating agents hosted on Azure AI Foundry with tools (File Search, Code Interpreter, Bing Grounding, Azure AI...
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agentic-jujutsu
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Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
agent-factory
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Claude Code agent generation system that creates custom agents and sub-agents with enhanced YAML frontmatter, tool access patterns, and MCP integration support following proven production patterns
Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
agent-memory-systems
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Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector...
computer-use-agents
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Build AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and...
debugging
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Systematic debugging methodology with root cause analysis. Phases: investigate, hypothesize, validate, verify. Capabilities: backward call stack tracing, multi-layer validation, verification...
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
debugging-master
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Systematic debugging methodology - scientific method, hypothesis testing, and root cause analysis that works across all technologiesUse when "bug, debugging, not working, broken, investigate, root...
Design patterns for building autonomous coding agents. Covers tool integration, permission systems, browser automation, and human-in-the-loop workflows. Use when building AI agents, designing tool...
debugging-dags
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Comprehensive DAG failure diagnosis and root cause analysis. Use for complex debugging requests requiring deep investigation like "diagnose and fix the pipeline", "full root cause analysis", "why...
agent-based-modeling
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Design and implement agent-based models (ABM) for simulating complex systems with emergent behavior from individual agent interactions. Use when "agent-based, multi-agent, emergent behavior, swarm...
computer-use-agents
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Build AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and...
sub-agents
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Create and configure Claude Code sub-agents with custom prompts, tools, and models
agent-tool-builder
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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than...
parallel-agents
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Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.