Agent-Native Architecture

About

This skill provides a comprehensive framework for architecting software designed for AI agents. It shifts the development paradigm from writing rigid, hardcoded features to defining outcomes achieved by agents through atomic tool composition. By following principles like parity between UI and agent capabilities, developers can build self-modifying, highly flexible systems that exhibit emergent behaviors and improve through prompt refinement and accumulated context rather than just manual code deployments.

Key Features

• Framework for achieving action parity between human UIs and agent tools
• Best practices for designing composable Model Context Protocol (MCP) tools
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• Patterns for self-modifying systems and dynamic context injection
• Guidance on building atomic primitives to enable emergent agent capabilities
• Strategies for implementing autonomous execution loops and completion signals

Use Cases

• Designing extensible MCP toolsets that allow agents to replicate complex UI interactions
• Architecting autonomous systems that manage files, workflows, or data without human intervention
• Refactoring legacy codebases into prompt-native applications that evolve through context