What problem does it solve? AI coding agents produce poor output when they receive too little context (hallucinated APIs, ignored conventions) or too much context (lost focus, degraded quality). This Skill provides a structured methodology for curating exactly what the agent sees at each stage of a session. ## 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 task-relevant files, specs, and error output without flooding the context window. - Confusion Management: Defines explicit patterns for surfacing spec conflicts, missing requirements, and ambiguity instead of letting the agent silently guess. - Use Case: When starting a new feature, you load only the relevant spec section, the files to modify, one existing pattern example, and a constraints list, keeping focused context under 2,000 lines per task. ## Quick Start Ask the agent to help you create a CLAUDE.md rules file covering your tech stack, commands, conventions, and boundaries before starting your next coding session.
