nykooi1/vibe-wise

A Claude Code / Codex plugin that helps you learn how to build while AI writes the code.

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nykooi1/vibe-wise has 3.5k+ stars and 100+ forks on GitHub, is written in Python, and was last pushed on Oct 9, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 6 minutes ago
Added to GitGenius on October 8th, 2026
Created on September 29th, 2026
Open Issues & Pull Requests: 24 (+0)
GitHub issues: Enabled
Number of forks: 149
Total Stargazers: 3,739 (+1)
Total Subscribers: 13 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 0.7 hours
Mean response time: 34.5 hours
90th percentile: 7.1 days
Tracked items: 5

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Issue Activity (beta)

Open issues: 9
New in 7 days: 2
Closed in 7 days: 0
Avg open age: 2 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 2
Closed in 7 days: 0
Comments in 7 days: 1
Events in 7 days: 5

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Detailed Description

VibeWise is a Claude Code plugin that helps you learn how to build while AI writes the code.

The tool addresses the gap between wanting to learn software design and the temptation to let AI handle everything without understanding the reasoning. VibeWise keeps you in control by asking you to articulate your approach first, examining tradeoffs together, and explaining unfamiliar concepts before implementation begins. Claude writes the code only after you've shaped the design and approved it, then explains what changed and why. The workflow uses three checkpoints: Build, where you reason through the approach; Design, where you review and confirm the architecture; and Implementation, where you authorize specific code changes.

The plugin suits anyone learning to build—aspiring engineers, junior developers, or experienced engineers exploring unfamiliar stacks. It works whether you're starting fresh or joining an existing repository; for existing projects, Claude inspects the codebase and sketches a system map first. You need an up-to-date Claude Code installation and Python 3; no additional packages are required. Installation happens through the Anthropic Directory or GitHub marketplace, with setup taking just a few questions answered through arrow keys and Enter.

Development on the project shows consistent, focused activity with regular commits addressing specific improvements and bug fixes. The maintainer responds promptly to issues and pull requests, indicating active engagement with users. Updates are released at a steady pace, suggesting the tool is actively maintained and refined based on feedback. The codebase remains lean and purposeful, avoiding unnecessary complexity while supporting the core learning-first workflow.