What problem does it solve? Writing effective system prompts, custom modes, and skills is difficult: instructions are often too rigid and brittle, or too vague to guide model behavior. This Skill provides a structured methodology for finding the right balance between specificity and flexibility when authoring AI instructions. ## Core Features & Use Cases - Altitude Calibration: Helps you avoid overly prescriptive hardcoded rules and overly generic guidance by targeting the "Goldilocks zone" of instruction specificity. - Token-Efficient Prompt Design: Teaches how to minimize token count while maximizing signal, using canonical examples instead of exhaustive edge-case lists. - Structured Prompt Organization: Provides section templates (Background, Instructions, Tool Guidance, Output Format, Examples) and few-shot example structures for clear, maintainable prompts. - Use Case: When creating a new custom mode for a migration workflow, apply this Skill to define the expertise, core objective, constraints, and 2-3 canonical examples so the mode behaves consistently without brittle if-else logic. ## Quick Start Use the context-engineering skill to review and improve the system prompt for my new custom mode.
