Recently, I have been using OpenCode in conjunction with OpenSpec for secondary development on existing projects. I encountered some pitfalls and recorded them here:

1. Initialize Project:

First, run the CLI command in the project root directory to create the basic directory structure required by OpenSpec.

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# openspec init 
Note: OpenSpec collects anonymous usage stats. Opt out: OPENSPEC_TELEMETRY=0
Detected tool directories: OpenCode (pre-selected for first-time setup)
✔ Select tools to set up (24 available) OpenCode
▌ OpenSpec structure created
✔ Setup complete for OpenCode

OpenSpec Setup Complete

Created: OpenCode
4 skills and 4 commands in .opencode/
Config: openspec/config.yaml (schema: spec-driven)

Getting started:
  Start your first change: /opsx:propose "your idea"

Learn more: https://github.com/Fission-AI/OpenSpec
Feedback:   https://github.com/Fission-AI/OpenSpec/issues

Restart your IDE for slash commands to take effect.

Additionally, to understand OpenSpec more deeply, it is recommended to enable all OpenSpec extension features for direct use in OpenCode or Claude Code later. You need to restart OpenCode or Claude Code after modification:

Kaku is a terminal emulator for macOS featuring built-in AI assistant capabilities, integrating various AI tools such as Claude Code, Codex, Gemini CLI, Copilot CLI, and Kimi Code. This article details the installation, configuration, and best practices for Kaku, helping developers fully leverage the potential of AI-assisted programming.

Kaku Tool Introduction

What is Kaku

Kaku is a terminal emulator for macOS. It not only provides powerful terminal features but also includes built-in AI assistant capabilities, helping developers quickly complete tasks such as command diagnosis, code explanation, and AI conversations.

I. Background

With rapid business development, the current offline analysis data warehouse Doris cluster is facing resource contention issues due to diverse computing needs such as daily data science jobs, offline batch processing, and customer-side report queries. To address this, resource limits need to be implemented for different account resource requests. After research, the official Doris Workload Group solution has been adopted.

Doris version: doris-2.1.8-1-834d802457

II. Workload Group Introduction

Workload Group is an in-process resource isolation mechanism provided by Apache Doris that achieves resource isolation between different business loads through fine-grained division of CPU, memory, and IO resources within BE processes.

In the previous article “What is SDD,” we explored the importance of Specification-Driven Development. This article provides an in-depth comparison of two mainstream SDD tools—OpenSpec and Spec-Kit—to help developers choose the right tool for their needs.

Overview of OpenSpec and Spec-Kit

Introduction to OpenSpec

OpenSpec is a Specification-Driven Development (SDD) framework developed by Fission AI, designed specifically for AI coding assistants.

With the rising popularity of AI programming tools, a crucial concept is reshaping how we collaborate with AI to write code—SDD (Specification-Driven Development). This article will delve into the core philosophy of SDD and why mainstream AI programming tools are choosing to support the SDD model.

What is SDD

Definition of SDD

Specification-Driven Development (SDD) is a software development methodology that emphasizes writing clear, precise specifications before writing code, and then strictly implementing code according to those specifications.

With business expansion and the diversification of product forms, there is a need to deploy multiple sets of offline and real-time data warehouse clusters. While the previous Ansible Playbook method for deploying Doris FE/BE was basically sufficient, it fell short for subsequent Doris version upgrades, scaling, visual management, and onboarding junior operations personnel. Therefore, this document was written to facilitate quick future reference.

1. Overview

1.1 Introduction to Doris Manager

Doris Manager is a graphical operation and maintenance tool launched by the Apache Doris community for unified deployment, management, and monitoring of Doris clusters. It simplifies the entire process from operating system initialization and component deployment to daily operation and maintenance management, making it particularly suitable for rapidly setting up and maintaining large-scale Doris clusters in production environments.

Claude Code is the official AI coding tool launched by Anthropic. It can read codebases, edit files, run commands, and integrate with development tools. It excels in complex reasoning and code understanding, making it one of the most powerful AI coding tools available today.

Detailed Introduction to Claude Code

What is Claude Code

Claude Code is an AI-driven agent coding assistant that helps developers build features, fix bugs, and automate development tasks. It understands the entire codebase and can work across multiple files and tools to complete tasks.

OpenCode Overview

What is OpenCode

OpenCode is an open-source AI coding assistant built on VSCode with the following features:

• Open Source & Free: Fully open source, self-hostable
• Flexible Models: Supports multiple LLM backends
• Local First: Protects code privacy
• Highly Customizable: Extensible and customizable

Core Features

I. OpenCode Installation and Configuration

System Requirements

Operating System:
  - Windows 10/11
  - macOS 11+
  - Linux (Ubuntu 20.04+, CentOS 8+)

Hardware Requirements:
  - CPU: 4 cores+
  - RAM: 8GB+
  - Storage: 2GB available space

Software Dependencies:
  - Node.js 16+ (if building from source)
  - Git

Installation Steps

Method 1: Using Pre-built Versions (Recommended)

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# 1. Download OpenCode
# Visit https://github.com/opencode-org/opencode/releases
# Download the installer for your platform

# Linux/macOS
wget https://github.com/opencode-org/opencode/releases/latest/download/opencv-linux-x64.tar.gz
tar -xzf opencv-linux-x64.tar.gz
cd opencv
./opencode

# macOS (using Homebrew Cask)
brew install --cask opencode

# Windows
# Download opencv-setup.exe and run the installer

# 2. Launch OpenCode
# The welcome page will appear on first launch

Method 2: Building from Source

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# 1. Clone repository
git clone https://github.com/opencode-org/opencode.git
cd opencv

# 2. Install dependencies
npm install

# 3. Build project
npm run build

# 4. Run
npm run electron

Basic Configuration

settings.json Configuration