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 as conversations grow. This Skill provides a structured method for deciding what information an agent sees, when it sees it, and how it is structured across a session. ## Core Features & Use Cases - Five-Level Context Hierarchy: Organizes context from persistent rules files (CLAUDE.md, .cursorrules, AGENTS.md) down to transient error output and conversation history. - Context Budget Management: Trims deadweight at 75% window capacity, compresses failed attempts into summaries, and positions task-critical content last to counter the lost-in-the-middle effect. - Confusion Management: Surfaces spec-versus-code conflicts and missing requirements as explicit options instead of silently guessing. - Use Case: When starting a new feature, you create a rules file with your tech stack and conventions, load only the relevant spec section and source files, and restart cleanly at task boundaries with a recorded handoff state. ## Quick Start Set up a CLAUDE.md rules file for my project and show me how to structure context for the current task.
