---

name: vscode_integration description: Enables Mini-Agent to integrate directly with VS Code Chat API for seamless AI assistance version: "1.0.0" allowed_tools:

• list_skills
• get_skill
• execute_with_resources
• bash
• file_operations
• web_search architecture_pattern: "Progressive disclosure through skill system" integration_type: "Native Mini-Agent skill, not standalone extension"

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VS Code Integration Skill for Mini-Agent

Skill Metadata

• Name: vscode_integration
• Description: Enables Mini-Agent to integrate directly with VS Code Chat API for seamless AI assistance
• Allowed Tools: ["list_skills", "get_skill", "execute_with_resources", "bash", "file_operations", "web_search"]
• Architecture Pattern: Progressive disclosure through skill system
• Integration Type: Native Mini-Agent skill, not standalone extension

Overview

This skill enables Mini-Agent to provide AI assistance directly within VS Code's Chat interface using the Chat API. Instead of a separate extension, it integrates through Mini-Agent's native progressive skill system, leveraging the existing architecture patterns.

Architecture Design

Progressive Skill Implementation

Following Mini-Agent's intrinsic architecture:

CopyLevel 1: list_skills() → Discover VS Code integration skill
Level 2: get_skill() → Load full skill content and implementation
Level 3: execute_with_resources() → Provide Chat API integration

Integration Pattern

• Native Integration: Uses Mini-Agent's existing skill system
• Progressive Loading: Follows established disclosure patterns
• Context Preservation: Leverages knowledge graph for persistent state
• Tool Access: All Mini-Agent tools available through skill

Technical Implementation

Skill Loading Flow

1. Discovery: list_skills() reveals VS Code integration available
2. Content Load: get_skill() provides Chat API integration details
3. Execution: execute_with_resources() activates Chat API support

VS Code Chat API Integration

• Chat Participant: Registers as @mini-agent in VS Code Chat
• Message Handling: Processes chat requests through skill system
• Tool Execution: Routes tool calls through Mini-Agent's native system
• Response Streaming: Real-time updates to Chat interface

Session Management

• Context Tracking: Uses Mini-Agent's knowledge graph for session state
• Message History: Leverages existing workspace intelligence
• Tool Results: Standardized through Mini-Agent's ToolResult interface

Usage Patterns

Chat Interaction

Copy# Level 1: Discover VS Code integration
list_skills()

# Level 2: Load full Chat API integration
get_skill("vscode_integration")

# Level 3: Activate Chat API support
execute_with_resources("vscode_integration", mode="chat_api")

Available Commands in VS Code Chat

• @mini-agent explain this code - Code explanation with context
• @mini-agent generate test for function - Test generation
• @mini-agent refactor this code - Code refactoring
• @mini-agent search web for pattern - Web search integration
• @mini-agent use skill_name - Direct skill execution

Implementation Details

Chat API Integration Script

Copy# Activates VS Code Chat API support through Mini-Agent skill system
async def activate_vscode_chat_api():
    # Register chat participant
    participant = vscode.chat.createChatParticipant('mini-agent', handle_chat_request)
    
    # Route through Mini-Agent's skill system
    async def handle_chat_request(request, context, stream, token):
        # Process request through Mini-Agent's architecture
        response = await route_to_mini_agent_skill_system(request.prompt)
        stream.markdown(response)

Skill Integration Points

• Skill Loader: Uses existing skill loading infrastructure
• Tool Registry: Leverages Mini-Agent's tool ecosystem
• Knowledge Graph: Persistent context and session management
• Workspace Intelligence: Token management and context injection

Advantages of This Approach

Architecture Alignment

• Native Integration: Part of Mini-Agent's skill system, not external
• Progressive Enhancement: Follows established patterns
• Context Preservation: Uses knowledge graph for state management
• Modular Design: Clear separation through skill boundaries

Technical Benefits

• No Separate Extension: Integrated through existing Mini-Agent
• Unified Tool Access: All tools available through Chat
• Persistent Sessions: Leverages existing session management
• Quality Framework: Uses fact-checking and validation

User Experience

• Seamless Integration: Works within existing Mini-Agent workflows
• Consistent Behavior: Follows Mini-Agent interaction patterns
• Full Tool Access: Complete Mini-Agent functionality in Chat
• Context Awareness: Maintains workspace understanding

Configuration

Enable VS Code Integration

Copy# In Mini-Agent config or skill loading
skills_config = {
    "vscode_integration": {
        "enabled": True,
        "chat_participant": "@mini-agent",
        "auto_activate": True
    }
}

Workspace Integration

Copy# Automatic activation when VS Code detected
if workspace.contains_vscode_config():
    activate_vscode_integration_skill()

Error Handling

Graceful Degradation

• No VS Code: Skill remains available but inactive
• Chat API Missing: Falls back to standard Mini-Agent usage
• Tool Failures: Uses existing error handling patterns
• Session Issues: Leverages Mini-Agent's session management

Future Enhancement

Roadmap

1. Workspace Context: Automatic file and project awareness
2. Multi-Panel Support: Integration with multiple Chat panels
3. Custom Commands: User-defined Chat shortcuts
4. Performance Optimization: Token and context management

Integration Opportunities

• exai-mcp-server: Can extend Chat API to multi-tool systems
• orchestrator: Infrastructure Chat integration
• External Tools: Support for additional editor integrations

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Summary

This skill provides VS Code Chat API integration through Mini-Agent's native architecture, maintaining alignment with progressive skill loading, knowledge graph persistence, and modular design principles. It enables seamless AI assistance within VS Code while preserving Mini-Agent's core identity as a CLI/coder tool foundation.

Status: Ready for Level 2 implementation Confidence: High - follows established patterns Next: Load skill content and implement Chat API integration