Learn how Happy and T3 Code differ in their key features, development activity, technology stack and community adoption, so you can decide which of these ai coding agent orchestrators is best for you.
Last 30 days
Last commit
13 hours agoRepository age
1 yearVersion
1.2.5License
MITSelf-hosted
YesRepository
slopus/happy
Last 30 days
Last commit
12 hours agoRepository age
9 monthsVersion
v0.1.2License
MITRepository
pingdotgg/t3code
Both Happy and T3 Code have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, growth, activity, maturity, licensing and features when making your decision.
Both tools have similar popularity levels, with Happy having 24,302 stars and T3 Code having 29,901 stars on GitHub. In terms of developer contributions, T3 Code has 8,034 forks, indicating strong developer engagement.
T3 Code is growing faster, adding 6,342 stars in the last 30 days (+27%) against adding 83 stars for Happy (+0.3%). T3 Code is both larger and pulling further ahead.
Both projects show recent activity, with Happy last updated 13 hours ago and T3 Code 12 hours ago.
Both projects started around the same time, with Happy beginning 1 year ago and T3 Code 9 months ago.
Both projects use the MIT license, providing identical terms for usage and distribution.
Both tools serve similar use cases in AI Coding Agent Orchestrators.
Happy provides self-hosting options for complete data control and customization, while T3 Code may be primarily cloud-based or require different deployment approaches.