Project Development Methodology

About

This skill provides a comprehensive methodology for building robust LLM projects, ranging from initial task-model fit evaluation to complex multi-agent architectures. It emphasizes a structured pipeline approach—acquire, prepare, process, parse, and render—while utilizing the file system as a state machine for reliable, idempotent execution. Whether you are designing batch processing workflows or interactive agent applications, this skill helps optimize performance, manage costs, and ensure high-quality structured outputs through rapid prototyping and architectural reduction principles.

Key Features

• File system-based state management for idempotency and debugging
• Cost estimation and token usage optimization frameworks
• Guidance on choosing between single and multi-agent architectures
• Structured pipeline architecture design (Acquire to Render)
• 7,140 GitHub stars
• Task-model fit evaluation and manual prototyping strategies

Use Cases

• Designing a batch processing pipeline for large-scale data analysis
• Evaluating if a business requirement is better solved via traditional code or LLMs
• Architecting complex agent systems with context isolation and tool usage