Special Considerations¶

Async Context Managers¶

AgentPool and Agents use async context managers - always use async with:

async with AgentPool(manifest) as pool:
    async with pool.get_agent("name") as agent:
        result = await agent.run("prompt")

MCP Server Lifecycle¶

MCP servers are spawned as subprocesses - pool cleanup handles termination. Use ProcessManager from anyenv for external process management.

UPath for File Operations¶

Use UPath (universal_pathlib) not Path - supports remote filesystems (s3://, gs://, etc.)

Model Configuration¶

Prefer string shorthand in YAML: model: "openai:gpt-4o" Fallback models: type: fallback, models: [primary, backup]

Entry Points¶

The project uses entry points for extensibility: - agentpool_toolsets - Register custom toolsets - fsspec.specs - Filesystem implementations (ACP) - universal_pathlib.implementations - Path implementations