prompt-architecture

What problem does it solve?

This Skill reduces inconsistent agent behavior by turning fragile prompt writing into a structured, validated prompt architecture that holds up across thousands of runs, including adversarial inputs.

Core Features & Use Cases

• Three-layer prompt assembly: Separates system identity/constraints, user task payload, and assistant priming to prevent instruction collisions.
• Constrained output enforcement: Guides the model to emit schema-compliant outputs (for example, strict JSON) using validation-oriented scaffolding.
• Deterministic few-shot selection: Selects relevant examples dynamically to establish domain patterns while minimizing “prompt lottery” variability.
• Validation gate concept: Uses a structural preflight mindset to catch malformed or conflicting prompt components before execution.
• Use Case: When building a Google Ads analysis agent, use this Skill to ensure the agent reliably returns the same structured report format for the same input, even under instruction-injection attempts.

Quick Start

Ask your AI assistant to rewrite your current system and user prompts into a three-layer architecture with explicit constraints and a schema-validated output format for the task you’re running.