Summary

vibe-check guides beginners from vague app ideas to buildable plans, focusing on problem validation and user experience before coding. It targets individuals with app concepts but no coding experience, ensuring they build the right thing by rigorously validating the problem and user needs, significantly increasing project viability.

How It Works

This skill acts as an AI mentor, translating product management techniques (pain-mining, competitor analysis) into actionable steps. It uncovers and pressure-tests the core problem, maps user experience, identifies technical decisions, recommends a tech stack, and designs an integrated growth loop for organic acquisition. This approach prioritizes problem validation and user-centric design over premature implementation.

Quick Start & Requirements

Install via CLI (npx skills add TexasBedouin/vibe-check) or clone (git clone https://github.com/TexasBedouin/vibe-check .claude/skills/vibe-check). Primarily for AI coding tools like Claude Code; adaptable by copying instructions. No specific hardware or non-default software prerequisites are mentioned beyond the AI environment.

Highlighted Details

• Outputs a comprehensive plan: problem statements, user flows (mermaid), feature breakdowns (V1/V2+), architecture, tech stack, data models, cost estimates, checklists, and growth loops.
• Generates a visual HTML blueprint for human review.
• Includes "Checkup Mode" for safely tidying existing codebases.
• Teaches foundational coding concepts (Git, secrets) in beginner terms.
• Integrates a core growth loop strategy for organic user acquisition.
• Features semantic versioning (current: 1.8.0) with update checks.

Maintenance & Community

Built by Amer Arab, drawing inspiration from product development and AI leaders. The README lists influential concepts but lacks direct community channel links (Discord/Slack) or details on ongoing maintenance or sponsorships.

Licensing & Compatibility

Released under the permissive MIT license, allowing broad use, modification, and distribution. This suggests high compatibility for commercial and closed-source projects without significant restrictions.

Limitations & Caveats

Effectiveness depends on the paired AI coding tool. Translating product management concepts may present a learning curve for absolute beginners. The focus is strictly on planning and blueprinting; actual code generation quality relies on the AI's implementation.