agentic-ai-prompt-research

Why we included this project

The authors reverse-engineered how agentic coding assistants like Claude Code assemble their behavior, without any leaked internals. Everything here is reconstructed from behavioral observation, output analysis, and community discussions, and the repository is explicit that these are approximations rather than verbatim copies. That honesty makes it a useful reference for engineers designing their own agent coordination, context-window compaction, or tool-call approval logic. Researchers and educators get a structured breakdown of modern agent architecture that is easier to read than raw prompt dumps. It is a knowledge resource rather than runnable software, so treat it as a design reference before you start building.