OpenCode CLI Guide: AI-Powered Coding for Developers

AI-assisted development has moved past browser tabs and cumbersome IDE extensions. For Tier-1 engineers working in deep codebases, context switching is the ultimate productivity killer. You want your tools where your fingers already are: the command line.

OpenCode CLI is an open-source, terminal-native AI coding assistant designed for engineers who live in their shell. It indexes your repository, understands local context, and executes complex refactoring, debugging, and generation tasks directly from the command line without leaking your proprietary code to unwanted telemetry endpoints.

This guide covers installation, configuration, core workflows, advanced prompt engineering for the terminal, and production best practices for integrating OpenCode CLI into your daily development lifecycle.

Why Terminal-Native AI?

Modern IDE extensions like GitHub Copilot or Cursor are powerful, but they abstract away the plumbing. When you are managing multi-container Docker environments, running custom shell scripts, or operating over SSH on a remote development instance, GUI-based extensions fall short.

OpenCode CLI bridges this gap by offering:

• Zero Context Switching: Stay in your terminal emulator, tmux session, or SSH tunnel.
• Repository-Wide Awareness: It builds a lightweight abstract syntax tree (AST) and vector index of your local directory, letting you query the entire codebase instantly.
• Model Agnosticism: Bring your own API keys. Route requests to OpenAI, Anthropic (Claude 3.5 Sonnet), local models via Ollama, or enterprise gateways.
• Scriptability: Combine OpenCode commands with standard Unix pipes (grep, awk, jq) to automate repetitive developer workflows.

Installation and Setup

OpenCode CLI is distributed via standard package managers. Ensure you have Node.js (v18+) or Go installed depending on your distribution channel. For this guide, we will use the npm global installation method.

Step 1: Install the Package

Run the following command in your terminal to install the CLI globally:

npm install -g opencode-cli

Verify the installation by checking the version:

opencode --version

Step 2: Configure API Keys and Providers

OpenCode CLI requires access to an LLM provider. You can configure it interactively or by setting environment variables in your shell profile (.bashrc, .zshrc, or .config/fish/config.fish).

To run the interactive setup wizard:

opencode config init

Alternatively, set your preferred provider and API key directly via environment variables:

export OPENCODE_PROVIDER="anthropic"
export OPENCODE_MODEL="claude-3-5-sonnet-20241022"
export ANTHROPIC_API_KEY="sk-ant-..."

Step 3: Local Model Configuration (Ollama)

If you are working in a secure air-gapped environment or want zero data leakage, you can point OpenCode CLI to a local instance running via Ollama.

First, pull your model of choice:

ollama pull codellama:34b-instruct

Then configure OpenCode to use the local endpoint:

export OPENCODE_PROVIDER="ollama"
export OPENCODE_MODEL="codellama:34b-instruct"
export OPENCODE_ENDPOINT="http://localhost:11434"

Core Workflows and Commands

OpenCode CLI is built around intuitive subcommands that map to everyday engineering tasks.

1. Interactive REPL Mode

For exploratory coding, debugging, or brainstorming architectures, launch the interactive REPL session inside your project root:

opencode chat

Once inside the REPL, you can issue natural language commands, reference specific files using the @ symbol, or run slash commands:

• @src/auth/jwt.ts - Attach file context to your prompt.
• /explain - Break down the logic of the currently referenced file or function.
• /test - Generate unit tests for the active buffer.
• /clear - Reset the conversation context window.

2. Single-Shot Terminal Prompts

For quick answers, shell command generation, or minor script fixes, use the ask subcommand without entering the REPL:

opencode ask "Write a bash one-liner to find all dangling Docker volumes and delete them safely"

3. Automated Code Generation (opencode generate)

When you need to bootstrap a new module, API endpoint, or utility function based on existing codebase patterns, use the generate command:

opencode generate --prompt "Create a rate-limiting middleware in TypeScript using Redis" --output src/middleware/rateLimit.ts

The CLI will analyze existing database clients, configuration structures, and coding styles in your repository to ensure the generated code matches your team's conventions.

Advanced Usage: Context Management and Indexing

The quality of an LLM's output is directly proportional to the quality of its context window. OpenCode CLI includes a powerful indexing engine that parses your project structure.

Ignoring Files and Directories

To prevent the AI from indexing build artifacts, node modules, or sensitive configuration files, create an .opencodeignore file in your repository root, mirroring the syntax of .gitignore:

node_modules/
dist/
build/
*.log
.env*
secrets/

Forcing a Re-Index

If you have pulled a massive upstream branch or generated new boilerplate, force OpenCode to rebuild its local context cache:

opencode index --force

Refactoring and Debugging in Practice

Let’s walk through a real-world scenario: debugging a race condition in a Go microservice and refactoring it to use worker pools.

Step 1: Isolate the Problem

Navigate to your project directory and invoke OpenCode to analyze the suspect file:

opencode chat

In the prompt interface, type:

@internal/worker/pool.go Look for potential race conditions in the worker dispatch loop and explain how we can fix them using context cancellation.

Step 2: Apply the Refactor

Instead of manually rewriting the concurrency boilerplate, ask OpenCode to perform the refactor and write the changes directly to disk:

opencode refactor --file internal/worker/pool.go --instructions "Implement a buffered worker pool with graceful shutdown and context propagation."

Step 3: Verify and Test

Review the generated diff using standard Git tooling before committing:

git diff internal/worker/pool.go

Then, instruct OpenCode to write the accompanying unit tests:

opencode test --file internal/worker/pool.go --output internal/worker/pool_test.go

Integrating OpenCode into CI/CD and Git Hooks

Tier-1 engineering teams rely heavily on automation. You can integrate OpenCode CLI into your Git pre-commit hooks to automatically generate commit messages or run automated code reviews.

Automated Commit Messages

Create a Git alias or shell script in .git/hooks/prepare-commit-msg to draft meaningful commit messages based on your staged changes:

#!/bin/sh
# .git/hooks/prepare-commit-msg

COMMIT_MSG_FILE=$1
COMMIT_SOURCE=$2

if [ "$COMMIT_SOURCE" = "" ]; then
    DIFF=$(git diff --cached)
    SUMMARY=$(opencode ask "Write a conventional commit message (feat/fix/refactor) for the following diff:\n$DIFF")
    echo "$SUMMARY" > "$COMMIT_MSG_FILE"
fi

Make the hook executable:

chmod +x .git/hooks/prepare-commit-msg

Now, every time you run git commit, OpenCode will inspect your staged diff and write a descriptive, standards-compliant commit message automatically.

Security, Privacy, and Enterprise Considerations

When evaluating AI tooling for Tier-1 development environments, security is paramount. OpenCode CLI provides several safeguards to protect intellectual property:

• Local-First Indexing: Code parsing and AST generation happen locally on your machine. Only the relevant context chunks required for the active prompt are transmitted to the LLM API provider.
• No Training Opt-In: When using enterprise API tiers (such as Anthropic’s API or OpenAI’s Enterprise endpoints), your prompts and code are not used for model training.
• Custom Proxy Routing: If your organization routes all external traffic through an internal corporate API gateway or transparent proxy, configure OpenCode to use it:

export OPENCODE_ENDPOINT="https://ai-gateway.internal.mycompany.com/v1"

Troubleshooting Common Issues

Issue 1: Context Window Exhaustion

If your repository is massive, OpenCode may throw a token limit error when referencing entire directories.

• Solution: Narrow your context scope. Instead of referencing an entire module, target specific files or use .opencodeignore to filter out non-essential assets.

Issue 2: Slow Response Times with Remote Models

Network latency combined with large prompt payloads can slow down generation.

• Solution: Switch to a faster model variant for interactive tasks (e.g., claude-3-haiku or gpt-4o-mini) while reserving heavier models like Claude 3.5 Sonnet for complex architectural refactoring.

Conclusion

OpenCode CLI brings the power of state-of-the-art language models directly into the developer's natural habitat: the terminal. By eliminating context switches, respecting local repository structures, and integrating seamlessly into Unix workflows and Git hooks, it accelerates development velocity without sacrificing code quality or security.

Install it, configure your preferred provider, and start executing complex engineering tasks directly from your shell.