Add complete Kaizen Agentic framework foundation

- Essential project files: .gitignore, pyproject.toml, README.md
- Documentation framework: CHANGELOG.md, CONTRIBUTING.md, TODO.md, CLAUDE.md
- 15 specialized agent definitions for comprehensive development workflow
- Core source code structure with optimization framework
- Testing infrastructure with example tests
- Proper Python package structure following PythonVibes standards

This establishes the complete foundation for the AI agent development framework
with agent-driven workflows, continuous improvement principles, and comprehensive
development infrastructure.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

src/kaizen_agentic/core.py

@@ -0,0 +1,61 @@
+"""
+Core agent infrastructure for the Kaizen Agentic framework.
+
+This module provides the foundational classes for creating and managing
+AI agents with continuous improvement capabilities.
+"""
+
+from typing import Dict, Any, Optional
+from dataclasses import dataclass
+from abc import ABC, abstractmethod
+
+
+@dataclass
+class AgentConfig:
+    """Configuration for an AI agent."""
+
+    name: str
+    description: str
+    model: str = "inherit"
+    instructions: Optional[str] = None
+    metadata: Optional[Dict[str, Any]] = None
+
+    def __post_init__(self):
+        if self.metadata is None:
+            self.metadata = {}
+
+
+class Agent(ABC):
+    """Base class for AI agents in the Kaizen framework."""
+
+    def __init__(self, config: AgentConfig):
+        self.config = config
+        self.performance_history = []
+        self.optimization_data = {}
+
+    @abstractmethod
+    def execute(
+        self, task: str, context: Optional[Dict[str, Any]] = None
+    ) -> Dict[str, Any]:
+        """Execute a task and return results with performance metrics."""
+        pass
+
+    def record_performance(self, metrics: Dict[str, Any]) -> None:
+        """Record performance metrics for kaizen analysis."""
+        self.performance_history.append(metrics)
+
+    def get_optimization_data(self) -> Dict[str, Any]:
+        """Get data for optimization analysis."""
+        return {
+            "performance_history": self.performance_history,
+            "config": self.config,
+            "optimization_data": self.optimization_data,
+        }
+
+    def update_configuration(self, updates: Dict[str, Any]) -> None:
+        """Update agent configuration based on optimization insights."""
+        for key, value in updates.items():
+            if hasattr(self.config, key):
+                setattr(self.config, key, value)
+            else:
+                self.config.metadata[key] = value