Using Letta API for Self-Management

This skill provides runnable Python snippets for self-modification via the Letta API.

Setup

from letta_client import Letta client = Letta(base_url='https://api.letta.com')

Your agent ID (from environment or hardcoded)

import os AGENT_ID = os.environ.get('LETTA_AGENT_ID', 'agent-xxx')

Quick Reference

Task Reference File

Disable sleeptime, change model, update config self-management.md

Create, deploy, message subagents subagents.md

List, create, update, delete memory blocks memory-blocks.md

Common Patterns

Disable Sleeptime

client.agents.update(AGENT_ID, enable_sleeptime=False)

Message a Subagent

response = client.agents.messages.create( agent_id='agent-xxx-subagent-id', messages=[{'role': 'user', 'content': 'Your task here'}] ) print(response.messages[-1].content)

Update a Memory Block

client.agents.blocks.update( 'block-label', agent_id=AGENT_ID, value='New content here' )

When to Use API vs Other Methods

Method Use When

Letta API Modifying subagents, agent config, programmatic block updates

memfs (file edits) Updating your own memory blocks (auto-syncs)

Task tool Deploying subagents for work (preferred for most tasks)

Load the reference files as needed for detailed patterns.