# Phase 3: Error Handling & Validation

**Objective**: Handle errors and edge cases in agent workflows

## Key Error Scenarios

### 1. Tool Execution Failures

```python
def execute_tool_safely(tool_name: str, tool_input: Dict) -> Dict:
    """Execute tool with error handling."""
    try:
        tool_function = TOOL_FUNCTIONS[tool_name]
        result = tool_function(**tool_input)
        return {"success": True, "data": result}

    except Exception as e:
        logger.error(f"Tool {tool_name} failed: {e}")
        return {
            "success": False,
            "error": str(e),
            "message": "Tool execution failed. Please try again."
        }
```

### 2. Safety Refusals

```python
if response.stop_reason == "refusal":
    logger.warning("Agent refused request")
    # Don't retry - respect safety boundaries
    return {"error": "Request cannot be completed"}
```

### 3. Max Turns Exceeded

```python
if turn >= max_turns:
    logger.warning("Agent exceeded max turns")
    return {
        "error": "Task too complex",
        "partial_progress": extract_progress(messages)
    }
```

### 4. Invalid Tool Name

```python
# With strict mode, tool names are guaranteed valid
# But external factors can cause issues
if tool_name not in TOOL_FUNCTIONS:
    logger.error(f"Unknown tool: {tool_name}")
    return {"error": f"Tool {tool_name} not implemented"}
```

## Output

Robust error handling for production agent workflows.