agent-native-architecture

Design agent-native architectures where agents operate in iterative loops.

25|15|Updated Aug 2, 2021
One-click install
npx skills add https://github.com/JesusFilm/core --skill agent-native-architecture-jesusfilm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-native-architecture
Source: https://github.com/JesusFilm/core/tree/main/.claude/skills/agent-native-architecture
Command: npx skills add https://github.com/JesusFilm/core --skill agent-native-architecture-jesusfilm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

## What problem does it solve? Build and orchestrate agent-native architectures where agents are the primary executors and can work in iterative loops rather than hard-coded workflows.

## Core Features & Use Cases

  • Parity-driven design ensures every UI action has a corresponding agent capability.
  • Emphasizes atomic primitives, prompt-defined outcomes, and composability to enable emergent behaviors.
  • Provides reference patterns and governance guidance for designing MCP tools, self-modifying systems, and end-to-end agent-native apps.

### Quick Start Start by loading the architecture references and initialize an agent loop using atomic tools and a dynamic system prompt.

Frequently Asked Questions about agent-native-architecture

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is agent-native architecture and how does it differ from standard workflows?▼

Agent-native architecture designs systems where agents are primary executors operating in iterative loops, moving away from hard-coded workflows. It uses atomic primitives and composability to enable emergent capabilities and self-modification.

How do I design agent loops with atomic primitives and dynamic prompts?▼

You design agent loops by loading architecture references and initializing the loop using atomic tools alongside a dynamic system prompt. This approach defines outcomes through prompts and ensures composability for emergent behaviors.

What does parity-driven design mean for agent capabilities?▼

Parity-driven design ensures every UI action has a corresponding agent capability. This maps user interactions directly to agent execution, maintaining functional consistency across interface and automated loops.

Can I build self-modifying agent systems using composability and governance files?▼

Yes, you can build self-modifying systems. The architecture provides reference patterns and governance files to guide designing MCP tools, enabling agents to evolve and improve over time through composability.

When should I use agent-native systems instead of hard-coded workflows?▼

Use agent-native systems when you need emergent capability, iterative improvement over time, and prompt-defined outcomes. Hard-coded workflows lack the composability and loop-driven execution required for autonomous domain tools.

Does agent-native architecture work with MCP tools and reference patterns?▼

Yes, it provides specific reference patterns and governance guidance for designing MCP tools. These components integrate directly into the agent loop, supporting end-to-end agent-native applications.