akillness letta
Letta is a leading agent framework in the 2026 AI agent engineering landscape (23.6k★).
When to use this skill
- Stateful agents with self-editing memory (MemGPT research lineage)
- Memory blocks (e.g. human/persona) the agent rewrites via memory tools
- Letta Code CLI: local terminal agent with skills + subagents + continual learning (npm i -g @letta-ai/letta-code)
- Letta API/server: REST + Python/TS SDKs for app integration
- Model-agnostic; model leaderboard published (leaderboard.letta.com)
- Agent File (.af) portable agent format; sleep-time compute for background memory maintenance
- Ecosystem overlap: agent-memory-architecture (this repo) covers memory design concepts and already references Letta as a backend — letta skill covers operating it concretely
Installation
npm install -g @letta-ai/letta-code # CLI; server SDKs: pip install letta-client / npm i @letta-ai/letta-client
Core API
import Letta from "@letta-ai/letta-client";
const client = new Letta({ apiKey: process.env.LETTA_API_KEY });
const agentState = await client.agents.create({
model: "openai/gpt-5.2",
memory_blocks: [{ label: "human", value: "Name: Timber..." }],
tools: ["web_search", "fetch_webpage"],
});
Instructions
Step 1: Initialize the environment
Verify you have Python installed and set up properly. Use the correct package manager (pip, npm, pnpm, uv) as specified in the installation section.
Step 2: Establish the agent flow
Architecture pattern: Agent = model + memory blocks + tools persisted server-side; memory edited by the agent itself (self-improving); ADE (Agent Development Environment) for inspection
Step 3: Implement tool integrations and policies
Integrate necessary tools, environment keys, and safety gates according to your architectural needs. Position in the ecosystem: The stateful-memory agent lane; alternatives: mem0/graphiti (memory layers without agent runtime), deepagents (harness without self-editing memory)
Examples
Example 1: Minimal Agent Run
import Letta from "@letta-ai/letta-client";
const client = new Letta({ apiKey: process.env.LETTA_API_KEY });
const agentState = await client.agents.create({
model: "openai/gpt-5.2",
memory_blocks: [{ label: "human", value: "Name: Timber..." }],
tools: ["web_search", "fetch_webpage"],
});
Best practices
- Follow the primary installation commands for Letta to ensure dependencies are resolved correctly.
- Configure model providers and API keys securely before starting the runtime.
- Use appropriate sandboxing or permission isolation if executing AI-generated code.