egoist/waku

⚡ A native app for all your coding agents.

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Summary Information

Updated 58 minutes ago
Added to GitGenius on August 31st, 2026
Created on July 31st, 2026
Open Issues & Pull Requests: 132 (+0)
Number of forks: 148
Total Stargazers: 1,299 (+0)
Total Subscribers: 4 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 3.0 hours
Mean response time: 46.8 hours
90th percentile: 8.1 days
Tracked items: 39

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 94% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Almost all tracked open issues have seen activity in the last three months. Only 12% of issues opened in the past year have been closed. Three people close 80% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 86
New in 7 days: 25
Closed in 7 days: 8
Avg open age: 12 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 18
Closed in 7 days: 4
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (2)

Detailed Description

Waku is a native application that provides a unified interface for interacting with multiple coding agents.

The tool addresses the fragmentation problem of working with different AI coding assistants by offering a single native application where developers can access various coding agents. Rather than switching between browser tabs or separate applications for different agents, Waku consolidates these interactions into one place. The application is built in Rust, which enables it to run as a performant native app across platforms.

Waku suits developers who regularly use multiple coding agents and want to streamline their workflow by reducing context switching. It works best for teams or individuals who have adopted AI-assisted coding as part of their development process and need a centralized hub. The project positions itself as compatible with agents like Claude Code, Cursor, and others in the coding agent ecosystem, making it relevant for developers already invested in these tools.

The project shows active development with regular commits and ongoing refinement of its core functionality. The codebase demonstrates consistent attention to the native application architecture, with the Rust foundation being actively maintained and improved. The project maintains engagement with its feature set, incorporating feedback and expanding agent compatibility over time.