docs: clarify Auto Memory proposes memory updates and skills (#26527)

docs/cli/auto-memory.md

@@ -1,9 +1,10 @@
 # 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](./skills.md). You review, accept, or discard each extracted skill
-before it becomes available to future sessions.
+in the background and proposes durable memory updates and reusable
+[Agent Skills](./skills.md). You review each candidate before it becomes
+available to future sessions: apply memory updates, promote skills, or discard
+anything you do not want.
 
 <!-- prettier-ignore -->
 > [!NOTE]
@@ -12,28 +13,33 @@ before it becomes available to future sessions.
 ## 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.
+Memory scans those transcripts for durable facts, preferences, workflow
+constraints, and procedural patterns that recur across sessions. It can draft
+memory updates as unified diff `.patch` files and draft reusable procedures as
+`SKILL.md` files. All candidates are held in a project-local inbox until you
+approve or discard them.
 
 You'll use Auto Memory when you want to:
 
 - **Capture team workflows** that you find yourself walking the agent through
   more than once.
+- **Preserve durable project context** such as repeated verification commands,
+  local constraints, or personal project notes.
 - **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](../tools/memory.md), which captures single facts into
-`GEMINI.md`. Auto Memory captures multi-step procedures into skills.
+`GEMINI.md` when the agent explicitly calls it. Auto Memory infers candidates
+from past sessions, writes reviewable patches or skill drafts, and never applies
+them without your approval.
 
 ## 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.
+- At least one idle project session with 10 or more user messages. Auto Memory
+  ignores active, trivial, and sub-agent sessions.
 
 ## How to enable Auto Memory
 
@@ -66,36 +72,45 @@ UI, consume your interactive turns, or surface tool prompts.
     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.
+    a time. A state file records processed session versions, and extraction is
+    throttled so short back-to-back CLI launches do not repeatedly scan history.
+3.  **Candidate extraction.** A background extraction agent reviews the session
+    index, reads any sessions that look like they contain durable memory or
+    repeated procedural workflows, and drafts candidates. It defaults to
+    creating no artifacts unless the evidence is strong, so many runs produce no
+    inbox items.
+4.  **Safety boundaries.** Auto Memory writes candidates to a review inbox. It
+    cannot directly edit active memory files, settings, credentials, or project
+    `GEMINI.md` files.
+5.  **Patch validation.** Skill update patches are parsed and dry-run before
+    they are surfaced. Memory patches are parsed, target-allowlisted, and
+    applied atomically only when you approve them from the inbox.
+6.  **Notification.** When a run produces new candidates, Gemini CLI surfaces an
+    inline message telling you how many items are waiting.
 
-## How to review extracted skills
+## How to review extracted items
 
 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:
+The dialog groups pending items into new skills, skill updates, and memory
+updates. 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.
+- **Review** memory diffs before they touch active files.
+- **Apply** or dismiss private and global memory patches. Private patches target
+  the project memory directory; global patches target only your personal
+  `~/.gemini/GEMINI.md` file.
 
 Promoted skills become discoverable in the next session and follow the standard
-[skill discovery precedence](./skills.md#skill-discovery-tiers).
+[skill discovery precedence](./skills.md#skill-discovery-tiers). Applied memory
+patches update the underlying memory files and reload memory for the current
+session.
 
 ## How to disable Auto Memory
 
@@ -117,19 +132,26 @@ start. Existing inbox items remain on disk; you can either drain them with
 ## 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.
+  machine.
+- Auto Memory uses model calls to analyze selected local transcript content
+  during extraction. No candidates are applied automatically, but transcript
+  excerpts may be sent to the configured model as part of those calls.
+- The extraction agent is instructed to redact secrets, tokens, and credentials
+  it encounters and to never copy large tool outputs verbatim.
+- Drafted skills and memory patches live in your project's memory directory
+  until you promote, apply, dismiss, 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.
+- The extraction 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 memory or skills from the current session. It
+  only considers sessions that have been idle for three hours or more.
+- Project or workspace shared instructions in project `GEMINI.md` files are not
+  auto-extractable. Auto Memory can propose private project memory, global
+  personal memory, and skills.
 - 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.
@@ -138,6 +160,6 @@ start. Existing inbox items remain on disk; you can either drain them with
 
 - Learn how skills are discovered and activated in [Agent Skills](./skills.md).
 - Explore the [memory management tutorial](./tutorials/memory-management.md) for
-  the complementary `save_memory` and `GEMINI.md` workflows.
+  the complementary explicit-memory and `GEMINI.md` workflows.
 - Review the experimental settings catalog in
   [Settings](./settings.md#experimental).

docs/cli/tutorials/memory-management.md

@@ -125,4 +125,4 @@ immediately. Force a reload with:
   `/memory` options.
 - Read the technical spec for [Project context](../../cli/gemini-md.md).
 - Try the experimental [Auto Memory](../auto-memory.md) feature to extract
-  reusable skills from your past sessions automatically.
+  memory updates and reusable skills from your past sessions automatically.