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Bwai Advisor

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johnku2011
bwai-advisor

Use before scaffolding a bwai project — runs the full startup-goal workflow then recommends the right boilerplate and outputs the exact bwai new command to run.

Overview

Publisherjohnku2011
Repositoryboilerplates-with-ai-skills
Skill namebwai-advisor
Stars
239
Forks
24
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 johnku2011 on GitHub. Read the source before you install it.

Installation

Install the Bwai Advisor 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.
    https://github.com/johnku2011/boilerplates-with-ai-skills/tree/main/shared/skills/bwai-advisor
  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/johnku2011/boilerplates-with-ai-skills.git /tmp/boilerplates-with-ai-skills
mkdir -p .claude/skills
cp -r /tmp/boilerplates-with-ai-skills/shared/skills/bwai-advisor .claude/skills/bwai-advisor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bwai Advisor 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 Bwai Advisor 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 Bwai Advisor 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.

bwai Advisor

Use this skill when you have a product idea but haven't scaffolded yet. It runs the full startup-goal workflow to shape your goal, then maps the output to the right bwai boilerplate and gives you the exact command to run.

Required Companion Skill

  • startup-goal — runs first; the full intake loop, role subagents, and decision log are all startup-goal's responsibility. bwai-advisor adds only the final scaffold recommendation on top.

If startup-goal is unavailable, stop and tell the user to install both:

bash
npx bwai-cli install-skill bwai-advisor --global

That command installs bwai-advisor and its companion startup-goal into the user's global agent skill directories.

Mode Choice

At the start, pick a mode (ask once if unclear):

ModeWhenWhat you run
Full (default)Idea is fuzzy; need PRD + rolesFull startup-goal, then scaffold recommendation
Quick pickStack/product type is already clear, or user asks only for a boilerplateSkip role bench; recommend from signals + catalog

Also use Quick pick when the user says the idea doc is an approved brief.

Idea Document Input

If the user points at a markdown (or other) idea brief — via @file.md, a path, or "read this doc" — treat that file as the starting hypothesis:

  1. Read the file before asking intake questions.
  2. Skip questions the document already answers clearly.
  3. Only ask about missing or ambiguous high-risk unknowns.

How to Run (Full mode)

  1. Follow the startup-goal skill — intake loop, role subagents, decision log.
  2. Once the decision log is ready, continue to Scaffold Recommendation.

Scaffold Recommendation

After the brief is ready, choose a boilerplate using live catalog data when available, then fall back to the table below.

Prefer live catalog

If the bwai / bwai-cli CLI is available, run:

bash
bwai list-boilerplates

Use the printed names, stacks, and descriptions to pick the best match for the goal. Prefer an exact catalog name over inventing a new one.

Fallback mapping (when CLI is unavailable)

Pick the first row that matches:

If the goal is…Boilerplate
An AI product — chat, tools, structured LLM outputs on Next.jsnextjs-ai-app
A web product that needs a UI — React, Next.js, full-stack (no AI SDK)nextjs-app
A REST or HTTP API in Node where raw performance mattersfastify-api
A REST or HTTP API in Node where middleware and ecosystem matterexpress-api
A Python service, data pipeline, ML endpoint, or FastAPI projectpython-service
A mobile app targeting iOS and/or Androidreact-native-app
A CLI tool, background worker, cron job, or pure Node servicenode-service

If no row matches: say so explicitly. Name the closest boilerplate and explain what it covers and what it doesn't. Do not silently force a bad fit.

Confidence

Always state confidence for the primary pick:

ConfidenceMeaning
HighStack and product shape match one boilerplate clearly
MediumTwo boilerplates could work; primary is a judgment call
LowPartial fit or missing catalog option; say what is missing

When confidence is Medium or Low, always include an Alternative with when to prefer it (e.g. API-only first vs full-stack UI).

Output Format

Append this block at the end of the decision log (or after the quick-pick summary):


Recommended scaffold

Mode: Full | Quick pick

Boilerplate: <name> — <one-line reason tied to the goal>

Confidence: High | Medium | Low — <one-line why>

Alternative: <name or "none"> — <when to prefer this>

Command:

bash
bwai new <boilerplate-name> ./<project-folder> --agents claude,cursor

After scaffold, continue with:

text
cd <project-folder>
$founding-engineer  implement the first slice from the decision log
$qa-lead            verify acceptance before calling the slice done

Keep fresh:

bash
bwai sync-upstream   # pull latest omni-skills content into the project

Once scaffolded, the project includes $startup-goal, $founding-engineer, $qa-lead, $cto, and $product-manager — pick up where you left off using those skills inside your new project.


Maintenance Note

The fallback mapping table is a last resort. Prefer bwai list-boilerplates. Update the table when the catalog changes and the CLI is not the primary source. The startup-goal workflow stays in the startup-goal skill and updates via bwai sync-upstream / global reinstall.

Frequently asked questions

What does the Bwai Advisor AI skill do?

Use before scaffolding a bwai project — runs the full startup-goal workflow then recommends the right boilerplate and outputs the exact bwai new command to run.

Why use Bwai Advisor on TypingMind?

Because you install it once and use it with any model. Bwai Advisor 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 Bwai Advisor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/johnku2011/boilerplates-with-ai-skills/tree/main/shared/skills/bwai-advisor. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bwai Advisor?

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 Bwai Advisor?

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

Is the Bwai Advisor AI skill free?

Yes. It is published on GitHub by johnku2011 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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