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Agent skill

Tour

by ThinkfleetAI in ThinkfleetAI/memmesh

Browse all stored MemMesh memories for a project/user, grouped by type/scope with full content.

Apache-2.0Auto-check passed

Install Tour

skills CLI
$ npx skills add ThinkfleetAI/memmesh --skill tour -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ThinkfleetAI/memmesh tour --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ThinkfleetAI/memmesh.git skills-src && mkdir -p .claude/skills && cp -r skills-src/integrations/memmesh-plugin/skills/tour .claude/skills/tour && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tour
GitHub stars
419
Token cost
~268 tokens
SKILL.md length
105 words
Files
1
Skills in repo
24
Repo updated
First seen
Licence
Apache-2.0

At a glance

Browse all stored MemMesh memories for a project/user, grouped by type/scope with full content.

  • Reviewing everything captured
  • SKILL.md covers Pull the set, Present it and Big memory sets
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Onboarding to a project

What it does

Tour is an agent skill from ThinkfleetAI/memmesh. Browse all stored MemMesh memories for a project/user, grouped by type/scope with full content. Use when reviewing everything captured, onboarding to a project, or getting an overview of decisions, conventions, and learnings.

Its SKILL.md is about 270 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Persistent, self-improving memory for AI agents. Local-first Rust memory engine with MCP support. The licence is Apache-2.0.

When your agent uses it

  • Reviewing everything captured
  • Onboarding to a project
  • Getting an overview of decisions

Example prompts

  • “/tour”

What it can do on your machine

Read from SKILL.md and the folder at commit bba48f8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are jsonc).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tour loads about 268 tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 105 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~268

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ThinkfleetAI/memmesh at commit bba48f8, republished under its Apache-2.0 licence (© ThinkfleetAI). 105 words, ~268 tokens.

Download SKILL.mdSave it as .claude/skills/tour/SKILL.md (or your agent's skills folder).
name
tour
description
Browse all stored MemMesh memories for a project/user, grouped by type/scope with full content. Use when reviewing everything captured, onboarding to a project, or getting an overview of decisions, conventions, and learnings.

tour

Show the full contents of memory, organized.

Pull the set

jsonc
{ "name": "memory_list", "arguments": { "projectId": "<repo>", "limit": 100 } }

For a personal overview, pass userId and scope: "user" instead.

Present it

Group by type (preference / fact / rule / decision / behavior_pattern / …), then within each show content with a short id prefix. Call out anything status: superseded separately so the user sees what's been replaced.

End with a one-line summary: total count and the type breakdown (that's exactly what the stats skill returns if you want the numbers).

Big memory sets

If memory_list hits the limit, page with offset, or narrow by scope / type. Suggest dream (consolidation) if the tour reveals lots of duplicates or contradictions.

© ThinkfleetAI, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in integrations/memmesh-plugin/skills/tour of ThinkfleetAI/memmesh.

Open the folder on GitHubat commit bba48f8

Compare with similar skills

Tour next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tour compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tour this skillThinkfleetAI/memmesh419—~268Automated safety check: PassApache-2.0
Mem0 Memory Tourmem0ai/mem067k—~652Automated safety check: PassApache-2.0
Memori Long-Term MemoryMemoriLabs/Memori17k—~2kAutomated safety check: NotesCustom licence
Memori Long-Term MemoryMemoriLabs/Memori17k—~2kAutomated safety check: PassApache-2.0
Memoryyc-software/qm15k—~1.2kAutomated safety check: PassMIT
Migrate NanoClaw Legacy Memorynanocoai/nanoclaw31k—~3.1kAutomated safety check: PassMIT

Similar skills

  • Mem0 Memory Tour

    mem0ai/mem0

    Shows every stored Mem0 memory grouped by category with full text, optionally across all projects or filtered by a search query.

    67k GitHub stars~652 tokensUpdated yesterday
    Agent WorkflowsAuto-check passed

  • Memori Long-Term Memory

    MemoriLabs/Memori

    Connects Claude Code to Memori Cloud for long-term memory, recalling stored context before substantive replies and saving new context afterward.

    17k GitHub stars~2k tokensUpdated 4 days ago
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  • Memori Long-Term Memory

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    Adds structured long-term memory to OpenClaw agents, built automatically from sessions, with tools the agent calls to recall facts, summaries and decisions.

    17k GitHub stars~2k tokensUpdated 4 days ago
    Agent WorkflowsAuto-check passed

  • Memory

    yc-software/qm

    Deliberately search, add to, or curate your long-term memory with the memory tool — beyond the automatic recall/capture every turn already does.

    15k GitHub stars~1.2k tokensUpdated today
    Agent WorkflowsAuto-check passed

  • Migrate NanoClaw Legacy Memory

    nanocoai/nanoclaw

    Moves legacy NanoClaw and Claude-native memory files into the shared memory tree and standing-instruction files, group by group, with approval before any move.

    31k GitHub stars~3.1k tokensUpdated yesterday
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  • Mem0 Project Tour

    mem0ai/mem0

    Shows everything mem0 has stored for the current project, grouped by category, with a compact search mode and an all-projects view.

    67k GitHub stars~1.6k tokensUpdated yesterday
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More from ThinkfleetAI/memmesh

All 24 skills in this repo

  • Behaviors

    ThinkfleetAI/memmesh

    Surface emergent behavior patterns MemMesh has mined from a subject's history — recurring habits nobody predefined, each with prevalence, stability, and the evidence behind it.

    419 GitHub stars~519 tokensUpdated 1 mo ago
    Auto-check passed

  • Benchmark

    ThinkfleetAI/memmesh

    Run MemMesh's competitive benchmark harness (LOCOMO / BEAM) to compare retrieval quality, tokens, latency, and cost against Mem0, Zep, full-context, and naive-RAG baselines.

    419 GitHub stars~460 tokensUpdated 1 mo ago
    Auto-check passed

  • Context Loader

    ThinkfleetAI/memmesh

    Load relevant MemMesh context before starting work — searches memory and, for a specific subject, assembles a token-budgeted bundle (profile + behavior patterns + forward predictions + top memories)…

    419 GitHub stars~530 tokensUpdated 1 mo ago
    Auto-check passed

  • Graph

    ThinkfleetAI/memmesh

    Query MemMesh's bi-temporal knowledge graph — multi-hop reasoning across entities, point-in-time "what did we believe on date X", and anticipatory retrieval via spreading activation.

    419 GitHub stars~611 tokensUpdated 1 mo ago
    Auto-check passed

  • Memmesh CLI

    ThinkfleetAI/memmesh

    MemMesh CLI + local MCP server — the zero-infra, no-API-key path to the same engine as the hosted SDK.

    419 GitHub stars~855 tokensUpdated 1 mo ago
    Auto-check passed

  • Memmesh SDK

    ThinkfleetAI/memmesh

    MemMesh TypeScript SDK reference (@thinkfleet/memory-sdk) for the hosted platform at app.memmesh.ai.

    419 GitHub stars~1.6k tokensUpdated 1 mo ago
    Auto-check passed

Questions about Tour

What does Tour do?

Browse all stored MemMesh memories for a project/user, grouped by type/scope with full content. Tour is an agent skill from ThinkfleetAI/memmesh. Browse all stored MemMesh memories for a project/user, grouped by type/scope with full content.

When should I use Tour?

Tour fits situations like: reviewing everything captured; onboarding to a project; getting an overview of decisions.

How do I install Tour in Claude Code?

Run `npx skills add ThinkfleetAI/memmesh --skill tour -a claude-code`. Or copy the skill folder (integrations/memmesh-plugin/skills/tour in ThinkfleetAI/memmesh) into .claude/skills/tour in your project. Claude Code loads it when a task matches its description.

How do I install Tour in Codex?

Run `npx skills add ThinkfleetAI/memmesh --skill tour -a codex`. Or copy the skill folder (integrations/memmesh-plugin/skills/tour in ThinkfleetAI/memmesh) into .agents/skills/tour in your project. Codex loads it when a task matches its description.

Can I use Tour in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ThinkfleetAI/memmesh --skill tour -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tour, .gemini/skills/tour, .github/skills/tour and .opencode/skills/tour in your project.

What does Tour need to run?

SKILL.md names no scripts, command-line tools or credentials: Tour is instructions for the agent only.

Does Tour access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Tour safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tour use?

Tour is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tour use?

About 268 tokens (SKILL.md is roughly 1.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Tour?

Skills that share tags, products or a category with Tour: Mem0 Memory Tour (mem0ai/mem0, 67k stars), Memori Long-Term Memory (MemoriLabs/Memori, 17k stars), Memori Long-Term Memory (MemoriLabs/Memori, 17k stars) and Memory (yc-software/qm, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tour?

ThinkfleetAI (a GitHub organization) maintains it in ThinkfleetAI/memmesh, which has 419 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on August 25, 2026.

Source: ThinkfleetAI/memmesh on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.