opencode-ai/opencode
opencode
A powerful AI coding agent. Built for the terminal.
Usage guide
opencode is an open-source project around claude, code, llm with 13,129 GitHub stars. This guide focuses on when to use it, how to install it, how to run the first example, and what to verify before adopting it.
Key features
- Implemented mainly in Go, useful for judging integration effort in a similar stack.
- GitHub detected the MIT repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.
- GitHub is the main evaluation surface; review the README, issues, and recent commits first.
Best for
- Evaluating opencode for Go AI workflows.
- Comparing a GitHub project with 13,129 stars and current repository activity.
Pros
- opencode has visible GitHub traction with 13,129 stars. Topics: ai, claude, code.
- The GitHub repository is the primary evaluation surface.
Cons
- Production fit still depends on documentation depth, issue activity, and release cadence.
- License review should confirm the MIT terms fit your use case.
Production readiness
opencode should be validated with its README, release history, open issues, and integration requirements before production use.
License risk
MIT is reported by GitHub; review the repository license before redistribution or commercial use.
opencode architecture preview
opencode's main path starts at the entry surface, runs through Coding agent runtime, combines OpenAI / Claude, Files / repository context, GitHub / Shell commands, and returns Code changes / developer feedback.
Entry
CLI / terminal entry
opencode is primarily entered through a developer command or terminal workflow.
git clone https://github.com/opencode-ai/opencode.git
Runtime
Coding agent runtime
The runtime reads developer intent, inspects repository context, plans edits, and returns code-oriented actions.
coding workflow
Model
OpenAI / Claude
Model calls are likely routed through OpenAI, Claude based on README and topic signals.
OpenAI, Claude
Context
Files / repository context
Context comes from Files / repository context, which constrains what the model or runtime can use.
Files / repository context
Tools
GitHub / Shell commands
Tool adapters let the runtime act outside the model through GitHub / Shell commands.
GitHub, Shell commands
Output
Code changes / developer feedback
The final result is code edits, explanations, repository actions, or developer-facing feedback.
coding output
Featured video
DevOps Toolbox
Opencode Is Probably The Best Coding Agent I've Ever Used
373,590 views · 2025-10-17
Install tutorial
Before you install
- Local build tools for compiling the project
- A clean working directory for the first test run
Check the runtime environment
opencode may require a local build toolchain. Check the compiler, package manager, and system dependencies first.
Get the project files
Start from the official repository or package so the first run matches the documented behavior.
$ git clone https://github.com/opencode-ai/opencode.gitInstall or build dependencies
No extra setup command was detected. Check the README before adding custom configuration.
Adoption guidance and sources
Practical use cases
Agent workflow prototype
Use it to validate task decomposition, tool calling, memory, tool permissions, and result review loops.
A powerful AI coding agent. Built for the terminal.
This is one of the documented reasons to evaluate opencode before choosing a stack.
Focus area: ai
This is one of the documented reasons to evaluate opencode before choosing a stack.
AI Agents project comparison
Compare opencode with similar projects before committing to a stack.
Before adopting
- Complete one clean-environment verification using the official opencode setup path.
- Review repository license, model weights, external services, and dependency terms for your use case.
- Check recent commits, release cadence, issue response, and documentation depth.
- Evaluate output quality, latency, resource usage, and recovery behavior with a small dataset.
Configuration notes
- Review README configuration notes before using production data.
Sources checked
These links are used to verify repository, documentation, or tutorial details. Review the source pages before adopting the project.
Troubleshooting
- If installation fails, first confirm the command is being run from the README-specified directory.
- If dependencies conflict, retry in a fresh virtual environment, container, or working directory.
- If output looks wrong, return to the smallest documented opencode example before adding complex data.
- For keys, model files, or external services, verify environment variables, local paths, and permissions one by one.
- Before production use, review recent updates, open issues, license terms, and safety boundaries.
What is opencode?
opencode is an open-source ai agents project. A powerful AI coding agent. Built for the terminal.
How do I install opencode?
Start with the official README. The first detected setup step is: git clone https://github.com/opencode-ai/opencode.git.
Is opencode beginner-friendly?
If you already know the Go ecosystem, start with the smallest example. Otherwise test it in an isolated environment first.
Can opencode be used commercially?
GitHub detected the MIT repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.
Does opencode need a GPU?
GPU requirements depend on the workload, model, and dataset size. Start with the smallest README example before scaling up.
How should I decide whether to adopt opencode?
Evaluate setup cost, maintenance activity, issue health, license terms, and fit with your real workflow.