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Tour

  • 65 installs
  • 62.5k repo stars
  • Updated August 5, 2026
  • mem0ai/mem0

Helps with ai & agent building tasks during AI-assisted development.

About

tour is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • tour
  • AI & Agent Building
  • AI-coding skill

Tour by the numbers

  • 65 all-time installs (skills.sh)
  • +12 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #6,058 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/mem0ai/mem0 --skill tour

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Listed on Skillselion
Installs65
repo stars62.5k
Last updatedAugust 5, 2026
Repositorymem0ai/mem0

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

Mem0 Project Tour

Show the user what mem0 has stored for the current project.

Cross-project mode

When invoked with --all-projects (e.g., /mem0:tour --all-projects or /mem0:tour --all-projects auth middleware), search across ALL projects:

1. Call get_memories with filters={"AND": [{"user_id": "<active_user_id>"}]}, page_size=200no `app_id` filter. 2. If a search query was also provided, run search_memories with query=<query>, filters={"AND": [{"user_id": "<active_user_id>"}]}, top_k=20 — again no app_id. 3. Group results by app_id first, then by category within each project. 4. Display:

   ## <app_id_1> (<N> memories) ← current
   **Architecture Decisions** — <memory content>
   ...

   ## <app_id_2> (<N> memories)
   ...

   <N> memories across <M> projects

5. Mark the current project with ← (current) in the heading.

If --all-projects is NOT present, use the standard single-project flow below.

Peek mode (compact search)

When /mem0:tour receives a search query argument (e.g., /mem0:tour auth middleware) WITHOUT --all-projects, run in peek mode — compact one-liner results:

1. Run 2 parallel search_memories calls:

  • Broad: query=<query>, filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}, top_k=10, rerank=true
  • Targeted: query=<query>, filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "decision"}}]}, top_k=5, rerank=true

2. Deduplicate by ID, display compact results:

   ## mem0 search: "<query>" (<N> results)

   1. [decision] Auth module uses JWT with RS256 keys (2025-05-15) [mem0:a3f8b2c1]
   2. [anti_pattern] Don't use symmetric HS256 — leaked in env (2025-05-10) [mem0:7e2d9f4a]
   3. [convention] All middleware in src/middleware/ (2025-05-08) [mem0:c4d5e6f7]

Format: <number>. [<type>] <content, 80 chars> (<date>) [mem0:<short_id>] 3. If no results: No memories matching "<query>" for project <project_id>.

If no query argument and no --all-projects flag, use the full tour flow below.

Execution

Step 1: Fetch ALL memories for this project

Call get_memories to fetch all memories for this project:

filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}, page_size=100

Step 2: Run supplementary semantic searches

In parallel, run these search_memories calls to get relevance-ranked results for key topics:

  • query="architecture decisions design choices", filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}, top_k=10, rerank=true
  • query="bugs errors failures anti-patterns", filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}, top_k=10, rerank=true
  • query="project setup tooling conventions preferences", filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}, top_k=10, rerank=true

Do NOT filter by `metadata.type` in these calls. The platform auto-assigns categories — filtering on metadata.type misses memories that were auto-categorized but don't have an explicit metadata.type.

Step 3: Merge and group

Merge all results by memory ID (deduplicate). For each memory, determine its group using this priority:

1. Platform `categories` field (array on each memory, auto-assigned by Mem0). Use the first category value. 2. `metadata.type` field (if present, set explicitly by hooks/agent). Use as fallback if no categories. 3. "other" bucket for memories with neither.

Map category names to display names:

Platform category / metadata.typeDisplay name
architecture decisions, architecture_decisions, decisionArchitecture Decisions
anti patterns, anti_patterns, anti_patternAnti-Patterns
task learnings, task_learnings, task_learningTask Learnings
coding conventions, coding_conventions, conventionCoding Conventions
user preferences, user_preferences, user_preferenceUser Preferences
project profile, project_profileProject Profile
tooling setup, tooling_setup, environmentalTooling & Setup
technology, professional_detailsTooling & Setup
session_stateSession State
compact_summaryCompact Summaries
anything elseOther

Step 4: Display results

Sort groups by descending memory count. For each group that has results, print:

## <display_name> (<count> memories)
- <full_memory_content> (score: <similarity_score_if_available>)
- ...

Show the full memory text for each entry — do NOT truncate. If a group has more than 10 entries, show top 10 by recency (or similarity score if from a search call) and note ... and <N> more.

For groups with zero results, skip them entirely — don't print empty groups.

Step 5: Print totals

<N> memories across <M> categories — project: <project_id>, branch: <active_branch>

Step 6: Empty state

If zero memories found for this project, print:

No memories stored yet for project <project_id>.
Run /mem0:onboard to import project files, or start working — mem0 captures learnings automatically.

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