How does this differ from traditional API design?

Agent-native design focuses on atomic primitives and action parity, allowing agents to compose complex outcomes via reasoning and loops rather than just executing rigid, pre-defined endpoints.

What is an agent-native architecture?

It is a software design pattern where applications are built specifically to be navigated and controlled by AI agents as first-class citizens, rather than just as an afterthought to the UI.

What is action parity in this context?

Action parity is the foundational principle that an AI agent should be able to achieve any outcome through its available tools that a human user can achieve through the application's graphical interface.

Can this skill help with existing projects?

Yes, it includes guidance on refactoring existing codebases to provide the necessary tool granularity and context injection required for agents to operate effectively.

Agent-Native Architecture

Name: Agent-Native Architecture
Author: jayteealao

byjayteealao

개발자 도구

Designs software systems where autonomous agents function as first-class citizens using atomic tools and prompt-driven features.

소개

This skill provides a comprehensive framework for building 'agent-native' applications, shifting the development paradigm from hard-coded features to agent-driven outcomes. By focusing on action parity, atomic primitives, and composability, it enables developers to create software that Claude Code and other agents can navigate as effectively as human users. It is ideal for developers building autonomous workflows, MCP tools, or self-modifying systems that need to support emergent capabilities and improve through context refinement rather than constant code deployments.

주요 기능

Prompt-Based Feature Composition
0 GitHub stars
Action Parity Framework
Atomic Tool Granularity Patterns
Self-Modification Safety Rails
Emergent Capability Discovery

사용 사례

Designing autonomous agents for complex multi-step workflows
Refactoring legacy applications to be 'agent-friendly' and compatible with Claude Code
Building self-evolving software systems that refine behavior through feedback loops

소개

주요 기능

Prompt-Based Feature Composition
0 GitHub stars
Action Parity Framework
Atomic Tool Granularity Patterns
Self-Modification Safety Rails
Emergent Capability Discovery

사용 사례

Designing autonomous agents for complex multi-step workflows
Refactoring legacy applications to be 'agent-friendly' and compatible with Claude Code
Building self-evolving software systems that refine behavior through feedback loops