Learn how OpenAI's new agentic primitives—Skills, hosted shell, and server-side compaction—solve reliability, execution, and context limits for long-running AI agents.

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OpenAI introduced three agentic primitives to solve common failures in long-running AI agents: Skills (versioned, reusable instruction sets that replace fragile system prompts), a hosted shell tool (managed container environment for code execution with dependency installation), and server-side compaction (automatic context window management through truncation). These primitives work together through the Responses API to enable agents that can perform sustained, multi-step work without hitting reliability, execution, or context limit issues. The guide includes practical Python examples showing how to define skills, use the shell environment, enable compaction, and combine all three features in a complete agent workflow.

OpenAI Agentic Primitives: Skills, Shell & Compaction Guide

What Are Agentic Primitives (And Why Do They Matter)?

Skills: Reusable Instructions Your Agent Can Actually Follow

The Upgraded Shell Tool: A Safe Place for Agents to Work

Server-Side Compaction: Never Hit Context Limits Again

Putting It All Together: A Complete Agent Loop

What This Means for the Future of AI Agents