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AI Coding Agents

Terminal-based AI coding agents that understand your codebase, execute commands, and help with complex multi-file edits.

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Available Services

OpenCode

Port: 3030 | Memory: 256 MB | Maturity: BetaOpen-source AI coding agent supporting 75+ LLM providers with terminal-based UI and web interface for collaborative AI-assisted development.Features:
  • Multi-model support (Claude, GPT, Gemini, local models)
  • Web UI and terminal interface
  • Session management
  • Collaborative development
Documentation

Claude Code

Port: N/A | Memory: 512 MB | Maturity: StableAnthropic’s agentic coding assistant that runs in the terminal. Understands entire codebases, executes commands, and handles complex multi-file edits.Features:
  • Claude Sonnet/Opus model support
  • Full codebase understanding
  • Command execution in sandboxed environment
  • Multi-file editing
Requires: ANTHROPIC_API_KEYDocumentation

OpenAI Codex CLI

Port: N/A | Memory: 256 MB | Maturity: BetaOpenAI’s lightweight coding agent running in the terminal. Uses OpenAI models to understand context, suggest edits, and execute commands.Features:
  • GPT-4 and GPT-3.5 support
  • Context-aware suggestions
  • Sandboxed command execution
  • Lightweight and fast
Requires: OPENAI_API_KEYDocumentation

Gemini CLI

Port: N/A | Memory: 256 MB | Maturity: BetaGoogle’s AI-powered command-line coding agent. Leverages Gemini models for code understanding, generation, and multi-file editing.Features:
  • Gemini Pro/Ultra model support
  • Long context understanding
  • Multi-file editing
  • Fast code generation
Requires: GOOGLE_API_KEY or GEMINI_API_KEYDocumentation

Kimi CLI

Port: N/A | Memory: 256 MB | Maturity: ExperimentalMoonshot AI’s command-line coding agent powered by the Kimi model. Strong multilingual and long-context capabilities.Features:
  • Kimi model with 200K+ context window
  • Multilingual support (Chinese, English)
  • Long-context understanding
  • Fast inference
Requires: KIMI_API_KEYDocumentation

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Usage Example

Add AI coding agents to your stack: 
npx create-better-openclaw --services opencode,claude-code,codex --yes
Use the Coding Team preset: 
npx create-better-openclaw --preset coding-team --yes

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Integration with OpenClaw

All coding agents integrate with OpenClaw through:
  • Shared workspace volumes
  • Environment variable configuration
  • API access for automation
  • Skill pack integration

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Comparison

ServiceProviderUIMemoryAPI Required
OpenCodeMulti-providerWeb + Terminal256 MBOptional
Claude CodeAnthropicTerminal512 MBRequired
Codex CLIOpenAITerminal256 MBRequired
Gemini CLIGoogleTerminal256 MBRequired
Kimi CLIMoonshotTerminal256 MBRequired

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Best Practices

  1. API Keys: Store API keys securely in .env files
  2. Workspace Sharing: Mount shared volumes for collaborative work
  3. Resource Allocation: Allocate sufficient memory for larger codebases
  4. Model Selection: Choose models based on task complexity and cost

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