What problem does it solve? AI coding agents produce inconsistent or hallucinated output when they receive too little context (inventing APIs, ignoring conventions) or too much (losing focus). This Skill provides a systematic method for deciding what information an agent sees, when it sees it, and how it is structured. ## Core Features & Use Cases - Five-Level Context Hierarchy: Organizes context from persistent rules files (CLAUDE.md, .cursorrules, AGENTS.md) down to transient conversation history, with templates for each level. - Context Packing Strategies: Provides the Brain Dump, Selective Include, and Hierarchical Summary patterns for loading exactly the right files, specs, and examples per task. - Confusion Management: Defines explicit patterns for surfacing spec conflicts, missing requirements, and ambiguity instead of silently guessing, plus an inline planning pattern for multi-step tasks. - Use Case: When starting a new feature in a large codebase, use this Skill to write a rules file covering tech stack, commands, and conventions, then load only the relevant spec section and one example pattern before each task. ## Quick Start Ask the agent to set up a context engineering structure for your project, including a rules file with tech stack, commands, conventions, and boundaries.
