Add 260+ Claude Code skills from skills.sh

Complete collection of AI agent skills including:
- Frontend Development (Vue, React, Next.js, Three.js)
- Backend Development (NestJS, FastAPI, Node.js)
- Mobile Development (React Native, Expo)
- Testing (E2E, frontend, webapp)
- DevOps (GitHub Actions, CI/CD)
- Marketing (SEO, copywriting, analytics)
- Security (binary analysis, vulnerability scanning)
- And many more...

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Co-Authored-By: Claude <noreply@anthropic.com>
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# Phase 2: Terminal Execution Enhancements - Research Document
## Research Summary
### Modular Tool System Architecture
Based on research of leading AI agent frameworks (AutoGen, Xaibo, ReAct patterns), here are key architectural patterns:
#### 1. Tool Abstraction Layer
```python
# Base tool interface
class Tool:
name: str
description: str
parameters: dict
async def execute(self, **kwargs) -> ToolResult:
pass
```
#### 2. Tool Registry Pattern
```python
class ToolRegistry:
def register(self, tool: Tool)
def get(self, name: str) -> Tool
def list_available(self) -> List[Tool]
def execute(self, tool_name: str, **kwargs) -> ToolResult
```
#### 3. ReAct Pattern Integration
- **Thought**: Agent reasoning about what to do
- **Action**: Selecting and executing a tool
- **Observation**: Result from tool execution
- **Iteration**: Loop until completion
#### 4. Key Features from Research
- **Xaibo**: Tool providers make Python functions available as tools
- **AutoGen**: Built-in `PythonCodeExecutionTool` with custom agent support
- **ReAct**: `agent_loop()` controller that parses reasoning and executes tools
- **Temporal**: Durable agents that evaluate available tools
### Implementation Plan for Phase 2
#### Task 2.1: Create Modular Tool System
1. **Base Tool Interface** - Abstract class for all tools
2. **Concrete Tool Implementations**:
- `ShellTool` - Execute shell commands
- `FileOperationTool` - File system operations
- `WebSearchTool` - Web search capabilities
- `CodeExecutionTool` - Python code execution
#### Task 2.2: Enhanced Intent Analysis
1. **Command Classification** - Better detection of command types
2. **Tool Selection** - Automatic tool selection based on intent
3. **Context Awareness** - Remember previous commands for suggestions
#### Task 2.3: Error Handling & Output Formatting
1. **Structured Error Responses** - Clear, actionable error messages
2. **Output Formatting** - Rich output with syntax highlighting
3. **Telemetry** - Track command success rates and patterns
## Sources
- [Xaibo - Modular AI Agent Framework](https://xaibo.ai/tutorial/getting-started/)
- [Microsoft AutoGen Framework](https://github.com/microsoft/autogen)
- [AutoGen Tools Documentation](https://microsoft.github.io/autogen/stable//user-guide/core-user-guide/components/tools.html)
- [ReAct Pattern Implementation](https://til.simonwillison.net/llms/python-react-pattern)
- [Multi-Agent Design Patterns](https://medium.com/aimonks/multi-agent-system-design-patterns-from-scratch-in-python-react-agents-e4480d099f38)