Summary

This repository offers a research-based reconstruction of prompt patterns, agent coordination, and security classifications employed by agentic AI coding assistants, exemplified by Claude Code. It targets AI engineers, researchers, and builders, providing insights into architectural designs for dynamic prompt assembly, multi-agent collaboration, and safe tool execution, derived from observable behavior.

How It Works

The project analyzes how agentic systems dynamically assemble master prompts from modular, cacheable prefixes and session-specific suffixes. It details orchestration patterns for coordinating specialized sub-agents, including verification, exploration, and agent creation agents. A key focus is the multi-stage security classification for autonomous tool execution, incorporating base rules, user overrides, and fallback reasoning for ambiguous cases. The approach reconstructs these mechanisms through behavioral observation and output analysis, offering educational insights rather than direct code.

Quick Start & Requirements

This repository documents research findings and reconstructed patterns; it does not provide a runnable tool or installation instructions.

Highlighted Details

• Catalogues over 30 reconstructed prompt patterns, including Core Identity, Orchestration, Specialized Agents, Security, Tool Descriptions, Utility, Context Window Management, Dynamic Behaviors, and Skills.
• Details a "Prompt Assembly Pipeline" separating stable, cacheable prefixes from dynamic, session-specific suffixes.
• Explains a multi-stage "Security Classification" for autonomous tool execution, featuring predefined rules, user-configurable overrides, and extended reasoning fallbacks.
• Outlines a "Memory Hierarchy Loading Order" supporting transitive file inclusion and conditional injection via path-based filtering.

Maintenance & Community

No specific details regarding maintenance, contributors, sponsorships, or community channels (e.g., Discord, Slack) are provided in the README.

Licensing & Compatibility

The README does not specify a license type or provide compatibility notes for commercial use.

Limitations & Caveats

The documented patterns are reconstructed approximations based on observable behavior and community discussions, not direct copies of proprietary systems. Actual implementations may differ significantly. This is an independent research project, not affiliated with or endorsed by Anthropic.