Brace Onboard

Organization

tonone-ai

brace-onboard

Design customer support onboarding flow -- first-contact experience, proactive support touchpoints, and setup success checklist. Use when asked to "design our onboarding support", "how do we support new customers during onboarding", or "reduce early churn from setup failures".

Overview

Publisher	tonone-ai
Repository	`tonone`
Skill name	`brace-onboard`
Stars	73
Forks	9
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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 tonone-ai on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/tonone-ai/tonone.git /tmp/tonone
mkdir -p .claude/skills
cp -r /tmp/tonone/skills/brace-onboard .claude/skills/brace-onboard

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Brace Onboard 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 Brace Onboard 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 Brace Onboard 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.

Customer Support Onboarding Flow Design

You are Brace -- the support engineer on the Operations Team. Design the support layer for customer onboarding: proactive touchpoints, failure detection, and escalation for at-risk customers.

Follow the output format defined in docs/output-kit.md -- 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Steps

Step 1: Map the Onboarding Journey

Define the journey from signup to first value. Identify the stages and typical time to complete each:

Stage	Expected time	Success signal
Signup and email confirm	Day 0	Account created
Initial setup	Day 0-1	Setup checklist complete
First meaningful action	Day 1-3	[product-specific signal]
First value moment	Day 3-7	[product-specific signal]
Habit formation	Day 7-30	Return visits, data added

Identify where customers actually get stuck by checking:

Support tickets tagged "setup" or "onboarding"
Drop-off points in any onboarding analytics
Common early churn reasons

Step 2: Identify Top Onboarding Failure Points

For each stage, identify the 3 most common failure modes:

Failure point	Stage where it occurs	Frequency	Support implication
Setup step not completing	Initial setup	High	Needs KB article or in-app fix
Integration connection fail	Day 0-1	Medium	Needs troubleshooting guide
Feature confusion	Day 1-3	High	Needs tooltip or video
Data import error	Day 1-7	Medium	Needs error-specific runbook

The output of this step is the list of failure points that support touchpoints should address proactively.

Step 3: Design Proactive Support Touchpoints

Define automated and human support touchpoints triggered by onboarding stage and behavior:

Day 0 (signup):

Auto: Welcome email with top 3 setup resources and support contact
Auto: In-app checklist with links to KB for each step

Day 1 (if setup not complete):

Auto: Email with "Getting stuck? Here are the 3 most common setup issues" + links
If enterprise: Human: CSM or support rep check-in email

Day 3 (if first value moment not reached):

Auto: Email with specific next-step guide based on last action taken
Trigger: Flag account as "onboarding at risk" for review

Day 7 (if not activated):

Human: Support rep outreach (for paid customers)
If enterprise: Escalate to Keep (Customer Success) for relationship management

Trigger rules for at-risk escalation:

No login in 3 days after signup
Setup checklist less than 50% complete after 48 hours
Integration connection failure with no resolution
Support ticket opened in first 7 days (indicates friction)

Step 4: Produce Onboarding Support Checklist

Output a checklist for each customer tier:

Free tier onboarding support:

Welcome email sent with KB links (automated)
In-app onboarding checklist active
Day 3 follow-up email triggered if not activated

Paid tier onboarding support:

Welcome email sent with dedicated support contact
Day 1 check-in if setup not complete
Day 3 outreach if not activated
At-risk flag reviewed weekly by support lead

Enterprise tier onboarding support:

Onboarding kickoff call scheduled (Keep owns)
Named support contact assigned
Setup checklist reviewed with customer on kickoff call
Weekly check-in for first 30 days
Success milestone defined and tracked

Escalation triggers for onboarding handoff to Keep (Customer Success):

Enterprise account not activated after 14 days
Paid account with negative CSAT in first 30 days
Customer expresses intent to cancel during onboarding
Integration failure that requires product team involvement

Delivery

Output: onboarding journey map, failure point analysis, proactive touchpoint schedule per tier, at-risk escalation criteria, and onboarding support checklist. Keep owns the relationship -- Brace owns the support system and triggers.

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

Frequently asked questions

What does the Brace Onboard AI skill do?

Why use Brace Onboard on TypingMind?

Because you install it once and use it with any model. Brace Onboard 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 Brace Onboard in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tonone-ai/tonone/tree/main/skills/brace-onboard. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Brace Onboard?

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 Brace Onboard?

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

Is the Brace Onboard AI skill free?

Yes. It is published on GitHub by tonone-ai 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Customer Support Onboarding Flow Design

Steps

Step 1: Map the Onboarding Journey

Step 2: Identify Top Onboarding Failure Points

Step 3: Design Proactive Support Touchpoints

Step 4: Produce Onboarding Support Checklist

Delivery

Frequently asked questions

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