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.