Before You Build logo

Before You Build

Organization
OneWave-AI
before-you-build

Use before starting a product, feature, MVP, agent, automation, or integration build to identify the main pre-build risk and choose the smallest validation step. Trigger when the user asks whether to build, scope, validate, prioritize, or sanity-check an idea before implementation.

Overview

PublisherOneWave-AI
Repositoryclaude-skills
Skill namebefore-you-build
Stars
293
Forks
49
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 OneWave-AI on GitHub. Read the source before you install it.

Installation

Install the Before You Build 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/OneWave-AI/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/before-you-build .claude/skills/before-you-build
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Before You Build 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 Before You Build 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 Before You Build 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.

Before You Build

Use this skill as a short pre-build risk gate.

The goal is to stop implementation from starting before the riskiest product assumption is clear. Stay implementation-agnostic: do not recommend stacks, architectures, tools, or code.

Core Behavior

When invoked:

  1. Restate the idea in one sentence.
  2. Identify the dominant pre-build risk.
  3. Give a short risk verdict.
  4. Recommend the smallest validation step that can reduce uncertainty before building.

Keep the response short unless the user explicitly asks for a deeper review.

Seven Risk Dimensions

Check the idea through these dimensions:

  • Demand risk: Do enough people already feel this problem strongly?
  • Buyer risk: Is there a clear person or team with reason to pay or commit?
  • Distribution risk: Is there a believable path to reaching those people?
  • Workflow risk: Does the idea fit how users already behave, decide, or work?
  • Timing risk: Is this urgent now, or only interesting in theory?
  • Trust risk: Does the product require data, access, behavior change, or credibility users may not grant?
  • Scope risk: Is the proposed build larger than the proof needed right now?

Pick the one or two risks that matter most. Do not turn every review into a long checklist.

Output Format

Use this format:

markdown
## Before You Build

Idea:
- [One-sentence restatement.]

Risk verdict:
- [Low / Medium / High risk] because [one concrete reason].

Main risk:
- [The dominant risk dimension and why it matters.]

Smallest validation step:
- [One specific action the user can take before building.]

Build guidance:
- [Build now / Build smaller / Validate first / Do not build yet.]

Validation Step Rules

The smallest validation step should be specific and low-cost.

Prefer steps like:

  • Talk to five target users who already tried to solve the problem.
  • Ask for payment, pre-order, letter of intent, or manual commitment before building software.
  • Run a landing page, waitlist, outbound message, or concierge test around one narrow promise.
  • Manually deliver the outcome once before automating it.
  • Test whether the missing feature blocks payment, retention, activation, or only completeness.
  • Find one repeated channel that can reach the target users before expanding scope.

Avoid steps like:

  • Build the MVP first.
  • Add more features to see what happens.
  • Choose a tech stack.
  • Design the architecture.
  • Write code.
  • Create a broad product roadmap.

Special Cases

If the idea is too vague, ask one clarification question:

text
Who is this for, what painful situation are they in, and how do they solve it today?

If the user is asking about a feature for an existing product, focus on whether the feature is a real blocker for payment, retention, activation, trust, or delivery.

If the user says the project is for learning, portfolio, or fun, do not judge it by startup standards. Focus on keeping scope small and making the learning outcome clear.

If the decision to build is already made and the user only wants implementation help, do not use this skill.

Style

Be direct, skeptical, and useful.

Do not be dismissive. The point is not to kill ideas; the point is to make the next build decision harder to fool yourself about.

Frequently asked questions

What does the Before You Build AI skill do?

Use before starting a product, feature, MVP, agent, automation, or integration build to identify the main pre-build risk and choose the smallest validation step. Trigger when the user asks whether to build, scope, validate, prioritize, or sanity-check an idea before implementation.

Why use Before You Build on TypingMind?

Because you install it once and use it with any model. Before You Build 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 Before You Build in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OneWave-AI/claude-skills/tree/main/before-you-build. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Before You Build?

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 Before You Build?

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

Is the Before You Build AI skill free?

Yes. It is published on GitHub by OneWave-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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