This skill implements the 'One Agent, One Prompt, One Purpose' principle, helping developers move away from inefficient 'god-mode' agents toward modular, high-performance specialist architectures. It provides a structured framework for defining agent scopes, selecting the minimum necessary context, choosing optimal models (Haiku, Sonnet, or Opus), and configuring task-specific toolsets. By reducing context confusion and maximizing the context window for specific tasks, this skill ensures that AI agents are more reproducible, easier to debug, and optimized for automated evaluation and integration into complex workflows.
Key Features
01Minimum Required Context (MRC) principle application to reduce noise
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03Structured templates for rapid creation of specialized agent personas
04Focused output format design for better downstream automation
05Task-to-Model mapping for cost and performance optimization
06One Agent One Prompt One Purpose architectural framework
