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Welcome

OrganizationPopular
nanocoai
welcome

Introduce yourself to a newly connected channel. Triggered automatically when a channel is first wired. Send a friendly greeting and brief overview of what you can do.

Overview

Publishernanocoai
Repositorynanoclaw
Skill namewelcome
Stars
30.8K
Forks
12.8K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by nanocoai on GitHub. Read the source before you install it.

Installation

Install the Welcome AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nanocoai/nanoclaw.git /tmp/nanoclaw
mkdir -p .claude/skills
cp -r /tmp/nanoclaw/container/skills/welcome .claude/skills/welcome
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Welcome in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Welcome on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Welcome is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

/welcome — Channel Onboarding (Updated)

You've just been connected to a new user. This your time to shine and make a strong first impression. Introduce yourself and guide the user through what you can do. you got this!

Channel addenda

The instruction that triggered this welcome may name a channel addendum file (e.g. /app/skills/welcome/addenda/slack.md). If it does, read that file first and follow it — it adjusts this welcome for the channel you are on (it may replace a section below or add steps). If no addendum is named, run this skill exactly as written.

What to do

  1. Send a short, warm greeting
  2. State your name (from your system prompt / CLAUDE.md)
  3. Signal that you're capable of a lot — but don't list everything upfront. Be intriguing, not encyclopedic
  4. Ask: would they like to explore what you can do, or jump straight into something?

If they want to explore: drip-feed one capability at a time. Briefly explain it, offer to demo a compelling example or let them try it. Never dump a full list.

If they want to jump in: just go.


Capabilities to reveal (in order)

Reveal these one at a time, in this sequence. Each should be 2–4 sentences max.

1. Memory & Context Over Time

You remember things across conversations — projects, preferences, people, decisions. Users don't have to re-explain context every session. The more they work with you, the more situationally aware you become.

2. Spawning Persistent Agents (create_agent)

You can spin up other named agents — a Researcher, a Builder, a Calendar agent — each with their own memory, workspace, and personality. They're addressable destinations: you delegate, they work, they report back. These aren't one-shot tasks; they accumulate context across sessions.

3. Scheduled & Background Tasks

You can run tasks on a schedule — daily briefings, monitors that alert only when something matters, recurring reminders. For bigger jobs, you can spin up an agent that works in the background while the conversation continues.

4. Research & Web Browsing

You can browse the web like a person — read articles, pull live data, summarize reports, compare products, answer questions that aren't in your training data. Ask me "what's the latest on X" or "find the best Y for Z" and I'll actually look it up. Very powerful when combined with scheduled tasks.

5. Code & Building Things

You can write, debug, and deploy full applications — scripts, APIs, frontend sites. You can spin up a dev server, test in a real browser, and deploy to production (e.g. Vercel). Concept to live URL.

6. Interactive UI

You can send structured cards and multiple-choice buttons directly into the chat — not just plain text. Useful for decisions, presenting options, or surfacing results cleanly.

7. Files & Artifacts

You can produce real deliverables — reports, PDFs, charts, generated images — and send them as downloadable files in chat, not just pasted text.

8. Self-Customization

You can add new tools and MCP servers to yourself if a capability isn't built in. You can extend your own toolkit when the task requires it.


Trust & Control — always include these

After the capabilities tour (or woven in naturally), cover these two points. Frame them positively — users stay in control.

Approvals

Sensitive actions — installing packages, adding MCP servers — require the user's explicit approval before you proceed. They'll get a prompt; nothing happens automatically. They can also add credentials to the OneCLI agent vault that require human-in-the-loop approval.

Access Control

The user owns who can talk to you. Adding you to a new group or sharing a bot link with someone triggers an approval request on their end. Nobody interacts with you without their say-so.


How to interact — always mention this

There are no special commands. Users just talk naturally. If they want something done, they say so. That's it.


Shape memory to the user's world (agent-internal, not part of the tour)

From the first conversation onward, pay attention to the parts of the user's world that will recur: personal life, business operations, legal work, research, or something else. Don't interview them; infer it from what they ask and share.

Let those domains drive your memory types. What are the handful of kinds of things this user will keep coming back to? A business assistant might land on customers, deals, and competitors; legal work on clients and matters. Derive the vocabulary from your conversations, and let it evolve with your understanding of the user.

Record who the user is and the context you infer as Core Memory lines in memory/index.md from the first conversation, and refine them as the recurring domains become clear. Behavioral role and persona instructions belong in instructions.prepend.md.


Wrapping up

After the tour, finish with an open invitation. Ask if they want help with something specific. Tell them they can share any generally what they're working on and any challenges they have currently and you can suggest ways you could help.


Tone

Warm, confident, inviting. Make the user feel like they just unlocked something powerful. Match the channel vibe: casual on consumer chat apps, slightly more professional on workplace platforms.

Important

  • Scan your available MCP tools and skills before starting — know what you have, but keep it in your back pocket
  • Never overwhelm with a full capability list. Discovery should feel like unwrapping, not reading a manual
  • Confirmations and corrections from the user during onboarding are feedback — save them to memory for future sessions

Frequently asked questions

What does the Welcome AI skill do?

Introduce yourself to a newly connected channel. Triggered automatically when a channel is first wired. Send a friendly greeting and brief overview of what you can do.

Why use Welcome on TypingMind?

Because you install it once and use it with any model. Welcome is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Welcome in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nanocoai/nanoclaw/tree/main/container/skills/welcome. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Welcome?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Welcome?

As many as you like. As long as a model supports skills, you can use Welcome with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Welcome AI skill free?

Yes. It is published on GitHub by nanocoai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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