What problem does it solve? AI coding agents produce inconsistent output when they lack the right context: they hallucinate APIs, ignore project conventions, and degrade in quality over long sessions. This Skill provides a structured methodology for feeding agents the right information at the right time. ## Core Features & Use Cases - Context Hierarchy Framework: Organizes context into five levels, from persistent rules files (AGENTS.md, .cursorrules, copilot-instructions.md) down to conversation history management. - Context Packing Strategies: Provides templates like the Brain Dump, Selective Include, and Hierarchical Summary for structuring task-specific context. - Confusion Management: Defines explicit patterns for surfacing spec conflicts and missing requirements instead of letting the agent guess. - Use Case: When starting a new project for AI-assisted development, use this Skill to create a rules file covering tech stack, commands, conventions, and boundaries so every agent session follows project standards. ## Quick Start Ask the agent to set up context engineering for this project by creating a rules file with the tech stack, commands, and code conventions.
