Agents

Autonomous systems that plan, use tools, execute code, and coordinate with other agents.

AS

Agentsbeginner

Agent Skills

Agent Skills package procedural knowledge as portable SKILL.md folders that any compatible agent discovers and loads on demand — teaching workflows, where MCP provides tools.

Agentsintermediate

Code Execution

Let LLMs generate and execute code in sandboxed environments for tasks requiring computational precision like data analysis and visualization.

MCP

Agentsintermediate

Model Context Protocol (MCP)

MCP is the open standard for connecting AI agents to external tools via a universal protocol, replacing one-off integrations with reusable servers.

Agentsadvanced

Multi-Agent Collaboration

Coordinate multiple specialized agents to solve complex tasks that exceed any single agent's capabilities using supervisor or peer topologies.

Agentsadvanced

Plan and Execute

Separate strategic planning from tactical execution by having one agent plan and another execute each step for more structured workflows.

Agentsintermediate

ReAct Loop

Interleave reasoning and action in a loop where the agent thinks, acts, observes, and repeats until the task is complete.

Agentsintermediate

Tool Calling

Let LLMs interact with external systems by emitting structured function calls that your code executes safely on their behalf.