Cline (VS Code) User Guide

I. Introduction

Cline (formerly Claude Dev) is a powerful VS Code AI programming assistant extension that supports multiple AI models. By integrating Nebula lab, you can flexibly switch between mainstream AI models to assist with programming, covering the entire development process including code generation, explanation, refactoring, and testing.

II. Quick Installation and Configuration

1. Install Extension

Search for "Cline" in the VS Code Extension Marketplace, click "Install" and enable it.

2. Configure Nebula API

Click the Cline Icon on the left side of VS Code to open the extension panel.

Click the settings button (gear icon) in the panel and select "OpenAI Compatible".

Fill in the configuration parameters:

Base URL: https://llm.ai-nebula.com/v1 (Fixed address)

API Key: Enter your Nebula Lab key (obtained from the Nebula Lab console)

Model Name: Enter the target model name (refer to "Recommended Models" below)

III. Recommended Models

🎯 Top Choice for Coding Development

Model ID	Features
`claude-sonnet-4-20250514`	Claude 4 latest version, extremely strong coding capability
`o4-mini`	OpenAI reasoning model, top choice for programming tasks
`gemini-2.5-pro`	Supports 2M context, strong multimodal capability
`deepseek-coder`	Code-specialized model, 128K context

💡 Complex Reasoning Tasks

Model ID	Features
`o3`	Latest reasoning model, significantly reduced price
`claude-sonnet-4-20250514-thinking`	Claude 4 Chain of Thought mode, transparent reasoning process
`deepseek-r1`	Latest reasoning model, 64K context
`grok-3-mini`	Lightweight model with reasoning capability

🚀 Fast Response

Model ID	Features
`gpt-3.5-turbo`	Classic model, high cost-performance ratio
`gemini-2.5-flash`	Fast speed, low cost, 1M context
`claude-3-haiku`	Lightweight fast version, 200K context
`gpt-4o-mini`	Lightweight fast version, 128K context

💰 High Cost-Performance Ratio

Model ID	Features
`deepseek-chat`	128K context, strong comprehensive capability
`qwen-turbo`	Alibaba Tongyi Qianwen Turbo version
`gpt-4.1-nano`	Ultra-low cost version, 128K context

IV. Core Functions

1. Intelligent Code Completion

Enter comments or code snippets, and AI automatically completes the implementation:

2. Code Explanation

After selecting a code snippet, use the following commands:

Cline: Explain Code: Explains code logic, purpose, and key steps.

Cline: Explain Error: Analyzes error messages, locates error causes, and provides fix suggestions.

3. Code Refactoring

Supports multiple refactoring scenarios:

Performance Optimization: Identifies redundant logic and inefficient algorithms, providing optimization plans.

Readability Improvement: Renames variables, splits complex functions, adds comments.

Issue Fixing: Automatically fixes syntax errors and logical vulnerabilities (e.g., null pointers, array out of bounds).

4. Generate Tests

Automatically generate unit tests based on functions:

V. Common Commands and Shortcuts

Command	Shortcut	Description
`Cline: Ask`	`Ctrl+Shift+L`	Ask AI (e.g., code questions)
`Cline: Explain`	`Ctrl+Shift+E`	Explain selected code
`Cline: Refactor`	`Ctrl+Shift+R`	Refactor selected code
`Cline: Generate`	`Ctrl+Shift+G`	Generate code based on requirements

VI. Advanced Functions

1. Multi-file Operations

Supports cross-file understanding and modification, for example:

"Move the formatDate function from utils.js to helpers.js and update all files referencing this function"

2. Architecture Design

Generate project architecture plans based on requirements:

Please design an architecture for an e-commerce backend management system, including:
- User management (login, permissions)
- Product management (CRUD, categories)
- Order processing (creation, payment, logistics)
- Data analysis (sales statistics, user profiling)
Tech stack: React + Node.js + PostgreSQL

3. Code Review

Automated PR review, covering multiple dimensions:

Review PR:
- Check if it conforms to ESLint standards
- Find potential bugs (e.g., unhandled exceptions)
- Performance optimization suggestions (e.g., duplicate calculation optimization)
- Security vulnerability scan (e.g., SQL injection risks)

VII. Usage Tips

1. Context Management

Provide detailed context to let AI generate more precise code:

2. Custom Prompts

Configure common prompt templates in VS Code settings:

{
  "cline.customPrompts": {
    "codeReview": "Review code, focusing on performance, security, and team code standards",
    "optimize": "Optimize code performance (reduce redundant calculations) and readability (add JSDoc comments)",
    "document": "Generate detailed Chinese documentation, including function description, parameter explanation, and usage examples"
  }
}

3. Project-Level Configuration

Create .cline/config.json in the project root directory to unify code style:

{
  "model": "claude-3-5-sonnet-20241022", // Default model
  "temperature": 0.7, // Generation randomness (0-1)
  "language": "zh-CN", // Prioritize Chinese interaction
  "codeStyle": {
    "naming": "camelCase", // Variable naming style
    "indent": 4, // Indentation spaces
    "quotes": "single" // String quote type
  }
}

VIII. Troubleshooting

Connection Failed

Check Configuration: Base URL must be https://llm.ai-nebula.com/v1, and API Key must be valid.

Verify Network: Turn off proxy or VPN and retry to ensure access to the API address.

Response Timeout

Optimization Plan: Use faster models (e.g., gemini-2.5-flash), split large tasks (e.g., "design function interface first, then implement logic").

Poor Generation Quality

Improvement Method: Add more context (e.g., tech stack, constraints), switch to more powerful models (e.g., claude-sonnet-4-20250514), clarify requirement details (avoid vague descriptions).

IX. Best Practices

1. Model Selection Strategy

Task Type	Recommended Model	Cost Level	Reason
Simple Completion	`gpt-3.5-turbo` / `gemini-2.5-flash`	Very Low	Fast speed, low cost, meets basic needs
Code Generation	`claude-sonnet-4-20250514` / `o4-mini`	Medium	Strongest coding capability, rigorous logic
Complex Reasoning	`o3` / `deepseek-r1`	Low-Mid	Strong reasoning capability, `o3` cost-performance optimized
Architecture Design	`deepseek-r1` + `claude-4-sonnet`	Low	Plan first then implement, balancing efficiency and cost
Code Review	`gemini-2.5-pro` / `claude-4-sonnet`	Medium	Long context support, understands multi-file associations
Batch Refactoring	`deepseek-chat` / `qwen-turbo`	Very Low	Fast processing of repetitive tasks, controllable cost
Doc Generation	`gpt-4.1` / `qwen-max`	Low-Mid	Natural and fluent expression, adapted for Chinese scenarios
Long Text	`gemini-2.5-pro` (2M Context)	Medium	Supports understanding of ultra-long codebases or documents

2. Prompt Optimization

❌ Bad Example: "Fix this function"

✅ Good Example:

"Fix the floating-point precision issue in the calculateTotal function, ensuring amounts are calculated to two decimal places (e.g., 1.995 should be rounded to 2.00)"

3. Progressive Development

Generate the basic framework first (e.g., function interfaces, component structure).

Gradually add core functions (implement step-by-step to avoid generating complex code at once).

Finally, optimize performance (e.g., caching, async processing) and error handling (e.g., boundary condition checks).

4. Security Awareness

Avoid including sensitive information (e.g., API keys, database passwords) in prompts.

Review AI-generated code (especially parts involving permissions and encryption).

Verify third-party dependency security (e.g., check vulnerabilities via npm audit).

X. Integration Workflow

1. Git Integration

2. Test-Driven Development (TDD)

Manually write test cases (e.g., Jest, PyTest).

Use Cline to generate implementation code that meets test requirements.

Run tests to verify, and use Cline to fix failing cases.

3. CI/CD Integration

Generate automated configuration files (e.g., GitHub Actions):

XI. Token Optimization and Cost Control

1. Monitoring and Management

Real-time Monitoring: View estimated token costs for the current session in the Cline sidebar.

Session Management: Keep sessions short (one session per task) to avoid meaningless accumulation of context.

2. Intelligent Model Switching Strategy

Planning Stage → DeepSeek-R1 or o3 (Strong reasoning, low cost)
Implementation Stage → Claude-4-Sonnet or o4-mini (Strongest coding capability)
Simple Tasks → GPT-3.5-Turbo or Gemini-2.5-Flash (Fast speed)
Long Text → Gemini-2.5-Pro (2M Context)

3. Configure Restriction Rules

Create a .clinerules file in the project root directory to constrain operation scope:

# Limit Cline operation scope
- Not allowed to modify node_modules directory
- Not allowed to delete important files marked in .gitignore
- Limit single modification file count ≤ 5
- Must prompt for confirmation before executing destructive operations (e.g., deleting code blocks)

4. Low-Cost Alternatives

GitHub Copilot Pro: $10/month, unlimited use, suitable for high-frequency scenarios.

Local Models (Ollama):

Domestic Models: qwen-turbo (Alibaba), glm-4 (Zhipu), ernie-4.0 (Baidu), low cost and adapted for Chinese scenarios.

XII. Advanced Best Practices

1. Plan/Act Modes

Plan Mode: Used for design and review (read-only, no changes), suitable for reasoning models (e.g., o3).

Act Mode: Directly implements code (can modify files), suitable for programming models (e.g., claude-sonnet-4).

Model Memory: Cline remembers preferences for both modes and automatically adapts to the scenario.

2. Context Management Skills

3. Avoid Token Explosion

❌ Wrong Practice: Handling multiple unrelated tasks in the same session, letting AI read entire large codebases, confusing context with frequent requirement changes.

✅ Correct Practice: Open a new session for each feature, include only relevant files, clarify requirements before starting, and commit code immediately after completion.

4. Workflow Optimization

# 1. Planning Stage (Reasoning Model)
"Use o3 or DeepSeek-R1 to analyze requirements and output architecture plans and interface designs"

# 2. Implementation Stage (Programming Model)
"Switch to Claude-4-Sonnet or o4-mini to generate core code by module"

# 3. Test Optimization (Fast Model)
"Use Gemini-2.5-Flash to generate unit tests and fix errors"

# 4. Documentation Stage (Comprehensive Model)
"Use GPT-4.1 to generate API documentation and usage instructions"

# 5. Code Review (Long Context Model)
"Use Gemini-2.5-Pro to review full project code and optimize details"

Cline (VS Code) AI Programming Assistant Integration Guide

Cline (VS Code) User Guide#

I. Introduction#

II. Quick Installation and Configuration#

1. Install Extension#

2. Configure Nebula API#

III. Recommended Models#

🎯 Top Choice for Coding Development#

💡 Complex Reasoning Tasks#

🚀 Fast Response#

💰 High Cost-Performance Ratio#

IV. Core Functions#

1. Intelligent Code Completion#

2. Code Explanation#

3. Code Refactoring#

4. Generate Tests#

V. Common Commands and Shortcuts#

VI. Advanced Functions#

1. Multi-file Operations#

2. Architecture Design#

3. Code Review#

VII. Usage Tips#

1. Context Management#

2. Custom Prompts#

3. Project-Level Configuration#

VIII. Troubleshooting#

Connection Failed#

Response Timeout#

Poor Generation Quality#

IX. Best Practices#

1. Model Selection Strategy#

2. Prompt Optimization#

3. Progressive Development#

4. Security Awareness#

X. Integration Workflow#

1. Git Integration#

2. Test-Driven Development (TDD)#

3. CI/CD Integration#

XI. Token Optimization and Cost Control#

1. Monitoring and Management#

2. Intelligent Model Switching Strategy#

3. Configure Restriction Rules#

4. Low-Cost Alternatives#

XII. Advanced Best Practices#

1. Plan/Act Modes#

2. Context Management Skills#

3. Avoid Token Explosion#

4. Workflow Optimization#