Files
admin b723e2bd7d Reorganize: Move all skills to skills/ folder
- Created skills/ directory
- Moved 272 skills to skills/ subfolder
- Kept agents/ at root level
- Kept installation scripts and docs at root level

Repository structure:
- skills/           - All 272 skills from skills.sh
- agents/           - Agent definitions
- *.sh, *.ps1       - Installation scripts
- README.md, etc.   - Documentation

Co-Authored-By: Claude <noreply@anthropic.com>
2026-01-23 18:05:17 +00:00

2.5 KiB

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

# Base tool interface
class Tool:
    name: str
    description: str
    parameters: dict

    async def execute(self, **kwargs) -> ToolResult:
        pass

2. Tool Registry Pattern

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