by tensorchord · Codex Skill · ★ 2.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Development environment for AI/ML <a href='https://coveralls.io/github/tensorcho
| Stars | 2,198 |
| Forks | 167 |
| Language | Go |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 66.7112801246289/100 |
| Open Issues | 130 |
| Last Updated | 2026-04-25 |
| Created | 2022-04-11 |
| Platforms | codex, docker, go |
| Est. Tokens | ~301k |
Looking for a envd alternative? If you're comparing envd with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Lightweight Native Local Dev Toolbox for Windows, macOS & Linux. Run Hermes Agent/OpenClaw/n8n/Apache/Nginx/C
AI Agent Development Platform - Supports multiple models (OpenAI/DeepSeek/Wenxin/Tongyi), knowledge base manag
Bytebot is a self-hosted AI desktop agent that automates computer tasks through natural language commands, ope
The first open-source agent skills builder. Define skills by vibe workflow, run on Claude Code, Cursor, Codex
:house: Home Assistant configuration & Documentation for my Smart House. Write-ups, videos, part lists, and l
The world's first open-source AI-native vector design tool and the first to feature concurrent Agent Teams. De
Explore other popular codex skill tools:
envd is 🏕️ Reproducible development environment for humans and agents. It is categorized as a Codex Skill with 2.2k GitHub stars.
envd is primarily written in Go. It covers topics such as agent, buildkit, code-agent.
You can find installation instructions and usage details in the envd GitHub repository at github.com/tensorchord/envd. The project has 2.2k stars and 167 forks, indicating an active community.
envd is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to envd on Agent Skills Hub include FlyEnv, LMForge-End-to-End-LLMOps-Platform-for-Multi-Model-Agents, bytebot. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.