Context Engineering Skill

What problem does it solve?

This Skill standardizes AI-to-AI communication by ensuring all prompts are grounded, task-focused, appropriately toned, aligned with long-term goals, and adhere to strict output constraints, preventing misinterpretations and drift.

Core Features & Use Cases

• Grounded Reality Check: Classifies claims as REAL, PARTIAL, or THEATER based on verifiable evidence like git logs or file existence.
• Task-First Structure: Ensures the core request is within the first 256 tokens, using a clear template for context and technical asks.
• Vibe Coding Tone: Adapts communication style to be collaborative for complex tasks and directive for routine ones.
• Architecture of the Gap: Explicitly addresses the tension between long-term vision (500-year) and immediate deliverables (90-day).
• Output Constraints: Enforces specific output formats (e.g., JSON) to prevent ambiguity.
• Use Case: When one AI needs to instruct another to perform a complex analysis or code integration, this Skill ensures the instructions are clear, verifiable, and aligned with project goals.

Quick Start

Apply the five filters to ensure your prompt is grounded, task-first, properly toned, telos-aligned, and constrained.