/tour
Browses all stored memories grouped by category with full content display. Use when reviewing all memories, exploring stored knowledge, onboarding to a new session, or getting an overview of what the agent remembers.
$ npx -y skills add mem0ai/mem0 --skill tour --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/tour
Context preview
The summary Claude sees to decide when to auto-load this skill.
Browses all stored memories grouped by category with full content display. Use when reviewing all memories, exploring stored knowledge, onboarding to a new session, or getting an overview of what the agent remembers.
SKILL.md
tour.SKILL.mdname: tour
description: Browses all stored memories grouped by category with full content display. Use when reviewing all memories, exploring stored knowledge, onboarding to a new session, or getting an overview of what the agent remembers.
Memory Tour
Show the user what Mem0 has stored — a full walkthrough of all memories grouped by category.
Cross-project mode
When invoked with `--all-projects` (e.g., `/mem0-tour --all-projects`), search across ALL projects:
1. Use `mem0_memory` tool with `action="get_all"`, `scope="global"` — no project filter. 2. Group results by project first, then by category within each project. 3. Display:
## <project_1> (<N> memories) <- current
**Goals** — <memory content>
...
## <project_2> (<N> memories)
...
<N> memories across <M> projects
4. Mark the current project with `<- current` in the heading.
If `--all-projects` is NOT present, use the standard single-project flow below.
Search mode
When `/mem0-tour` receives a search query argument (e.g., `/mem0-tour cooking recipes`), run in **search mode** — compact one-liner results:
1. Use `mem0_memory` tool with `action="search"`, `query=<query>`. 2. Display compact results (same format as the search skill). 3. If no results: `No memories matching "<query>".`
If no query argument and no `--all-projects` flag, use the full tour flow below.
Execution
Step 1: Fetch ALL memories
Use `mem0_memory` tool with `action="get_all"`.
Step 2: Group by category
Group memories using their `categories` field. Map to display names:
| Category | Display name | |---|---| | `identity` | Identity & Background | | `preferences` | Preferences | | `goals` | Goals & Aspirations | | `projects` | Projects & Initiatives | | `decisions` | Decisions | | `technical` | Technical Knowledge | | `relationships` | People & Relationships | | `routines` | Routines & Workflows | | `lessons` | Lessons Learned | | `work` | Work & Professional | | anything else | Other |
Step 3: Display results
Sort groups by descending memory count. For each group:
## <display_name> (<count> memories)
- <full_memory_content> (<date>)
- ...
Show the **full memory text** for each entry — do NOT truncate. If a group has more than 10 entries, show top 10 by recency and note `... and <N> more`.
Step 4: Print totals
<N> memories across <M> categories
Step 5: Empty state
If zero memories found:
No memories stored yet. Start a conversation — Mem0 captures learnings automatically, or use /mem0-remember to store something manually.
Read more
name: tour description: Browses all stored memories grouped by category with full content display. Use when reviewing all memories, exploring stored knowledge, onboarding to a new session, or getting an overview of what the agent remembers.
Memory Tour
Show the user what Mem0 has stored — a full walkthrough of all memories grouped by category.
Cross-project mode
When invoked with `--all-projects` (e.g., `/mem0-tour --all-projects`), search across ALL projects:
1. Use `mem0_memory` tool with `action="get_all"`, `scope="global"` — no project filter. 2. Group results by project first, then by category within each project. 3. Display:
## <project_1> (<N> memories) <- current **Goals** — <memory content> ... ## <project_2> (<N> memories) ... <N> memories across <M> projects
4. Mark the current project with `<- current` in the heading.
If `--all-projects` is NOT present, use the standard single-project flow below.
Search mode
When `/mem0-tour` receives a search query argument (e.g., `/mem0-tour cooking recipes`), run in **search mode** — compact one-liner results:
1. Use `mem0_memory` tool with `action="search"`, `query=<query>`. 2. Display compact results (same format as the search skill). 3. If no results: `No memories matching "<query>".`
If no query argument and no `--all-projects` flag, use the full tour flow below.
Execution
Step 1: Fetch ALL memories
Use `mem0_memory` tool with `action="get_all"`.
Step 2: Group by category
Group memories using their `categories` field. Map to display names:
| Category | Display name | |---|---| | `identity` | Identity & Background | | `preferences` | Preferences | | `goals` | Goals & Aspirations | | `projects` | Projects & Initiatives | | `decisions` | Decisions | | `technical` | Technical Knowledge | | `relationships` | People & Relationships | | `routines` | Routines & Workflows | | `lessons` | Lessons Learned | | `work` | Work & Professional | | anything else | Other |
Step 3: Display results
Sort groups by descending memory count. For each group:
## <display_name> (<count> memories) - <full_memory_content> (<date>) - ...
Show the **full memory text** for each entry — do NOT truncate. If a group has more than 10 entries, show top 10 by recency and note `... and <N> more`.
Step 4: Print totals
<N> memories across <M> categories
Step 5: Empty state
If zero memories found:
No memories stored yet. Start a conversation — Mem0 captures learnings automatically, or use /mem0-remember to store something manually.
Mem0 ("mem-zero") enhances AI assistants and agents with an intelligent memory layer, enabling personalized AI interactions.

