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agent-native-architecture

Design agent-native systems with atomic tools and prompt-defined outcomes.

Updated Mar 23, 2026
Search Tags:#prompt design#workflows#agent architecture#agent-native#autonomous systems
One-click install
npx skills add https://github.com/apollostreetcompany/codex-compound --skill agent-native-architecture-apollostreetcompany
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-native-architecture
Source: https://github.com/apollostreetcompany/codex-compound/tree/main/plugins/compound-engineering/skills/agent-native-architecture
Command: npx skills add https://github.com/apollostreetcompany/codex-compound --skill agent-native-architecture-apollostreetcompany

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill unit addresses the challenge of building applications where agents are first-class citizens, providing a framework for designing autonomous systems and efficient workflows.

Core Features & Use Cases

  • Parity: Ensures agents can achieve the same outcomes as UI actions.
  • Granularity: Uses atomic primitives for tools and prompt-defined outcomes for features.
  • Composability: New features can be added via prompts without code changes.
  • Emergent Capability: Agents can handle open-ended requests and discover latent demand.
  • Self-Modification: Agents can evolve over time through accumulated context and prompt refinement.
  • Use Case: Designing a system that organizes files, where the agent autonomously determines the best location based on file content and recency.

Quick Start

Install the 'agent-native-architecture' skill and start designing your agent-native system by defining atomic tools and writing system prompts that define desired outcomes.

Frequently Asked Questions about agent-native-architecture

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

FAQPage Schema
How do I design agent-native architecture for autonomous systems?▼

Agent-native architecture is built by treating agents as first-class citizens, ensuring parity between UI actions and agent capabilities, and using atomic tool primitives to enable autonomous systems and efficient workflows.

How do I build autonomous agent workflows that handle open-ended requests?▼

Build autonomous agent workflows by designing composability where new features are added via prompts without code changes, allowing agents to handle open-ended requests and discover latent demand through emergent capability.

What is the best way to achieve parity between UI actions and agent capabilities?▼

Achieve parity through agent-native architecture, which ensures agents can accomplish the same outcomes as UI actions by defining atomic tools and prompt-defined outcomes for features.

How do agents self-modify their behavior through prompt refinement?▼

Agents self-modify through accumulated context and prompt refinement, allowing them to evolve over time and autonomously determine outcomes like file organization based on content and recency without code changes.

Do I need prior architecture knowledge to build systems with agents as first-class citizens?▼

Yes, building systems with agents as first-class citizens requires a structured understanding of architecture principles and execution patterns to effectively define atomic tools and write system prompts.

When should I use atomic primitives for tool design in autonomous systems?▼

Use atomic primitives for tool design when you need high composability in autonomous systems, enabling new features to be added via prompts rather than requiring underlying code changes.

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