code-yeongyu/oh-my-openagent

OmO: Drop your tokens. Ultrawork. Done.

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Summary Information

Updated 55 minutes ago
Added to GitGenius on February 6th, 2026
Created on December 3rd, 2025
Open Issues & Pull Requests: 917 (-1)
GitHub issues: Enabled
Number of forks: 5,640
Total Stargazers: 68,665 (-2)
Total Subscribers: 231 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 13.4 hours
Mean response time: 6.8 days
90th percentile: 22.0 days
Tracked items: 2,596

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 96% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "question" is answered fastest, typically in about 4 hours, while "confirmed" waits about 7 days. 15% of tracked open issues have had no activity in three months. Only 9% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 519
New in 7 days: 53
Closed in 7 days: 33
Avg open age: 56 days
Stale 30+ days: 85
Stale 90+ days: 77

Recent activity

Opened in 7 days: 48
Closed in 7 days: 30
Comments in 7 days: 56
Events in 7 days: 139

Top labels

  • bug (875)
  • enhancement (331)
  • question (254)
  • triage:feature-request (148)
  • opencode (99)
  • answered (96)
  • triage:bug (96)
  • confirmed (85)

Detailed Description

oh-my-openagent is an agent harness for orchestrating multiple AI coding models across complex codebases.

The tool addresses the problem of being locked into single AI provider ecosystems by enabling developers to coordinate multiple models—including Claude, GPT, Gemini, and others—within a unified framework. Rather than relying on one vendor's closed environment, it allows you to route tasks to different models based on capability and cost, treating the AI landscape as an open market where models improve and become cheaper over time. The project includes LazyCodex as a simplified entry point for developers who want the multi-model orchestration without extensive setup.

The tool suits developers working on substantial codebases who want flexibility in which AI models they use and who are willing to manage a more complex setup than single-provider solutions. It is particularly relevant for teams that distrust vendor lock-in or need to optimize across multiple model providers. The README positions it against the walled-garden approach of proprietary coding assistants, emphasizing that the future belongs to orchestration across providers rather than picking a single winner.

The project maintains a substantial adopter base, with nearly all open issues coming from external users rather than the core team. Maintainers typically respond to new issues and pull requests within a day. The issue tracker is dominated by bug reports, enhancement requests, and user questions. The codebase is undergoing a multi-harness refactor to support multiple agent frameworks, and development happens transparently in the project's Discord community, with the maintainer building features and triaging work in real-time.