Migrating Memory logo

Migrating Memory

OrganizationPopular
letta-ai
migrating-memory

Migrate memory blocks from an existing agent to the current agent. Use when the user wants to copy or share memory from another agent, or during /init when setting up a new agent that should inherit memory from an existing one.

Overview

Publisherletta-ai
Repositoryletta-code
Skill namemigrating-memory
Stars
3.4K
Forks
411
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by letta-ai on GitHub. Read the source before you install it.

Installation

Install the Migrating Memory AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/letta-ai/letta-code.git /tmp/letta-code
mkdir -p .claude/skills
cp -r /tmp/letta-code/src/skills/builtin/migrating-memory .claude/skills/migrating-memory
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Migrating Memory in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Migrating Memory on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Migrating Memory is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Migrating Memory

This skill helps migrate memory blocks from an existing agent to a new agent, similar to macOS Migration Assistant for AI agents.

Requires Memory Filesystem (memfs)

This workflow is memfs-first. If memfs is enabled, do not use the legacy block commands — they can conflict with file-based edits.

To check: Look for a memory_filesystem block in your system prompt. If it shows a tree structure starting with /memory/ including a system/ directory, memfs is enabled.

To enable: Ask the user to run /memfs enable, then reload the CLI.

When to Use This Skill

  • User is setting up a new agent that should inherit memory from an existing one
  • User wants to share memory blocks across multiple agents
  • User is replacing an old agent with a new one
  • User mentions they have an existing agent with useful memory

Migration Method (memfs-first)

Export → Copy → Sync

This is the recommended flow:

  1. Export the source agent's memfs to a temp directory

    bash
    letta memory export --agent <source-agent-id> --out /tmp/letta-memory-<source-agent-id>
  2. Copy the files you want into your own memfs

    • system/ = attached blocks (always loaded)
    • root = detached blocks

    Example:

    bash
    cp -r /tmp/letta-memory-agent-abc123/system/project ~/.letta/agents/$LETTA_AGENT_ID/memory/system/
    cp /tmp/letta-memory-agent-abc123/notes.md ~/.letta/agents/$LETTA_AGENT_ID/memory/
  3. Commit and push the memory repo

    bash
    cd ~/.letta/agents/$LETTA_AGENT_ID/memory
    git add system/project notes.md
    git commit -m "Import memory from source agent"
    git push

This gives you full control over what you bring across and keeps everything consistent with memfs.

If MemFS Is Disabled

The legacy block-level CLI commands have been removed. Enable MemFS first, then use the export → copy → sync workflow above.

If you run into duplicate filenames while copying memory files, rename the incoming file or merge its contents manually before committing.

Workflow

Step 1: Identify Source Agent

Ask the user for the source agent's ID (e.g., agent-abc123).

If they don't know the ID, invoke the finding-agents skill to search:

Skill({ skill: "finding-agents" })

Example: "What's the ID of the agent you want to migrate memory from?"

Example: Migrating Project Memory

Scenario: You're a new agent and want to inherit memory from an existing agent "ProjectX-v1".

  1. Get source agent ID from user: User provides: agent-abc123

  2. Export their memfs:

    bash
    letta memory export --agent agent-abc123 --out /tmp/letta-memory-agent-abc123
  3. Copy the relevant files into your memfs:

    bash
    cp -r /tmp/letta-memory-agent-abc123/system/project ~/.letta/agents/$LETTA_AGENT_ID/memory/system/
  4. Commit and push:

    bash
    cd ~/.letta/agents/$LETTA_AGENT_ID/memory
    git add system/project
    git commit -m "Import project memory"
    git push

Frequently asked questions

What does the Migrating Memory AI skill do?

Migrate memory blocks from an existing agent to the current agent. Use when the user wants to copy or share memory from another agent, or during /init when setting up a new agent that should inherit memory from an existing one.

Why use Migrating Memory on TypingMind?

Because you install it once and use it with any model. Migrating Memory is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Migrating Memory in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/letta-ai/letta-code/tree/main/src/skills/builtin/migrating-memory. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Migrating Memory?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Migrating Memory?

As many as you like. As long as a model supports skills, you can use Migrating Memory with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Migrating Memory AI skill free?

Yes. It is published on GitHub by letta-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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