Auto Memory

Auto Memory is an experimental feature that mines your past Gemini CLI sessions in the background and turns recurring workflows into reusable Agent Skills. You review, accept, or discard each extracted skill before it becomes available to future sessions.

Note

This is an experimental feature currently under active development.

Overview

Every session you run with Gemini CLI is recorded locally as a transcript. Auto Memory scans those transcripts for procedural patterns that recur across sessions, then drafts each pattern as a SKILL.md file in a project-local inbox. You inspect the draft, decide whether it captures real expertise, and promote it to your global or workspace skills directory if you want it.

You’ll use Auto Memory when you want to:

• Capture team workflows that you find yourself walking the agent through more than once.
• Codify hard-won fixes for project-specific landmines so future sessions avoid them.
• Bootstrap a skills library without writing every SKILL.md by hand.

Auto Memory complements—but does not replace—the save_memory tool, which captures single facts into GEMINI.md. Auto Memory captures multi-step procedures into skills.

Prerequisites

• Gemini CLI installed and authenticated.
• At least 10 user messages across recent, idle sessions in the project. Auto Memory ignores active or trivial sessions.

How to enable Auto Memory

Auto Memory is off by default. Enable it in your settings file:

1. Open your global settings file at ~/.gemini/settings.json. If you only want Auto Memory in one project, edit .gemini/settings.json in that project instead.

2. Add the experimental flag:

   {
     "experimental": {
       "autoMemory": true
     }
   }

3. Restart Gemini CLI. The flag requires a restart because the extraction service starts during session boot.

How Auto Memory works

Auto Memory runs as a background task on session startup. It does not block the UI, consume your interactive turns, or surface tool prompts.

1. Eligibility scan. The service indexes recent sessions from ~/.gemini/tmp/<project>/chats/. Sessions are eligible only if they have been idle for at least three hours and contain at least 10 user messages.
2. Lock acquisition. A lock file in the project’s memory directory coordinates across multiple CLI instances so extraction runs at most once at a time.
3. Sub-agent extraction. A specialized sub-agent (named confucius) reviews the session index, reads any sessions that look like they contain repeated procedural workflows, and drafts new SKILL.md files. Its instructions tell it to default to creating zero skills unless the evidence is strong, so most runs produce no inbox items.
4. Patch validation. If the sub-agent proposes edits to skills outside the inbox (for example, an existing global skill), it writes a unified diff .patch file. Auto Memory dry-runs each patch and discards any that do not apply cleanly.
5. Notification. When a run produces new skills or patches, Gemini CLI surfaces an inline message telling you how many items are waiting.

How to review extracted skills

Use the /memory inbox slash command to open the inbox dialog at any time:

Command: /memory inbox

The dialog lists each draft skill with its name, description, and source sessions. From there you can:

• Read the full SKILL.md body before deciding.
• Promote a skill to your user (~/.gemini/skills/) or workspace (.gemini/skills/) directory.
• Discard a skill you do not want.
• Apply or reject a .patch proposal against an existing skill.

Promoted skills become discoverable in the next session and follow the standard skill discovery precedence.

How to disable Auto Memory

To turn off background extraction, set the flag back to false in your settings file and restart Gemini CLI:

{
  "experimental": {
    "autoMemory": false
  }
}

Disabling the flag stops the background service immediately on the next session start. Existing inbox items remain on disk; you can either drain them with /memory inbox first or remove the project memory directory manually.

Data and privacy

• Auto Memory only reads session files that already exist locally on your machine. Nothing is uploaded to Gemini outside the normal API calls the extraction sub-agent makes during its run.
• The sub-agent is instructed to redact secrets, tokens, and credentials it encounters and to never copy large tool outputs verbatim.
• Drafted skills live in your project’s memory directory until you promote or discard them. They are not automatically loaded into any session.

Limitations

• The sub-agent runs on a preview Gemini Flash model. Extraction quality depends on the model’s ability to recognize durable patterns versus one-off incidents.
• Auto Memory does not extract skills from the current session. It only considers sessions that have been idle for three hours or more.
• Inbox items are stored per project. Skills extracted in one workspace are not visible from another until you promote them to the user-scope skills directory.

Next steps

• Learn how skills are discovered and activated in Agent Skills.
• Explore the memory management tutorial for the complementary save_memory and GEMINI.md workflows.
• Review the experimental settings catalog in Settings.