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openai-assistants

Configure OpenAI Assistants, Threads, Messages, and Runs for stateful chatbots.

961|99|Updated Oct 20, 2025
Search Tags:#rag#openai#code-interpreter#conversational-ai#stateful-chat#assistants#file-search
One-click install
npx skills add https://github.com/jezweb/claude-skills --skill openai-assistants
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: openai-assistants
Source: https://github.com/jezweb/claude-skills/tree/main/skills/openai-assistants
Command: npx skills add https://github.com/jezweb/claude-skills --skill openai-assistants

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openai, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill eliminates the complexity of building conversational AI with memory, allowing you to create intelligent chatbots that maintain context across sessions without manual state management.

Core Features & Use Cases

  • Stateful Conversations: Maintains complete chat history automatically, enabling multi-turn dialogues that feel natural and contextual.
  • Built-in Tools: Provides Code Interpreter for data analysis, File Search for document Q&A, and Function Calling for custom integrations.
  • Use Case: Imagine you're building a customer support bot. Use this Skill to automatically track conversation history, execute Python code for calculations, and search through thousands of documents for relevant information.

Quick Start

Use the openai-assistants skill to create a math tutor that can solve equations step-by-step while remembering previous problems and explanations.

Key Benefits

  • 57% Token Savings: Reduces context overhead from ~14,000 to ~6,000 tokens per interaction.

Frequently Asked Questions about openai-assistants

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

FAQPage Schema
How do I build a stateful chatbot that remembers conversation history?▼

Stateful chatbots maintain complete conversation history automatically using Assistants, which track Messages and Runs across sessions. This eliminates manual state management and enables multi-turn dialogues with full context retention, reducing token overhead by 57% compared to traditional approaches.

Can I use OpenAI Assistants for document Q&A and file search?▼

Yes. OpenAI Assistants include a built-in File Search tool that searches through uploaded documents to answer questions. This is ideal for document Q&A workflows, allowing your assistant to retrieve relevant information from thousands of files without manual parsing.

How do I add code execution and custom functions to a conversational AI?▼

Assistants provide Code Interpreter for executing Python code during conversations and Function Calling for custom integrations. Together, they enable data analysis, calculations, and workflow automation within the same stateful chat interface.

What are the limits when building with OpenAI Assistants?▼

Assistants support up to 256k instruction characters, 100k messages per thread, 10-minute run duration, and 128 tools per assistant. Thread and message constraints scale with your use case; code execution and file search operate within OpenAI's standard rate limits.

Can I use Assistants for enterprise workflows like customer support or tutoring?▼

Yes. Assistants are designed for enterprise scenarios including customer support bots, tutoring systems, and data analysis workflows. Stateful conversations, file search, code execution, and function calling combine to handle complex, multi-step interactions across these domains.

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