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openai-assistants

Create and manage stateful AI agents with the OpenAI Assistants API v2.

3|Updated Nov 14, 2025
Search Tags:#rag#openai#chatbot#function calling#vector stores#assistants api#code interpreter
One-click install
npx skills add https://github.com/evolv3ai/claude-skills-archive --skill openai-assistants-evolv3ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: openai-assistants
Source: https://github.com/evolv3ai/claude-skills-archive/tree/main/skills/openai-assistants
Command: npx skills add https://github.com/evolv3ai/claude-skills-archive --skill openai-assistants-evolv3ai

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill simplifies the development of stateful AI applications by providing a robust framework for interacting with the OpenAI Assistants API, handling complex conversational flows, data analysis, and document retrieval.

Core Features & Use Cases

  • Stateful Chatbots: Build conversational agents that remember context across multiple turns using Threads.
  • Data Analysis & Visualization: Leverage the Code Interpreter tool to run Python code, process data, and generate charts directly within the conversation.
  • Document Q&A (RAG): Implement Retrieval-Augmented Generation using File Search and Vector Stores to answer questions based on your own documents (up to 10,000 files).
  • Custom Tool Integration: Extend AI capabilities with Function Calling to connect to external APIs and services.
  • Use Case: Create a customer support bot that can answer questions based on your product documentation, analyze uploaded user data for troubleshooting, and even execute code to test potential solutions.

Quick Start

Use the openai-assistants skill to create a math tutor assistant that solves equations using code interpreter.

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 using the OpenAI Assistants API?▼

Build stateful chatbots by creating assistants and managing conversation history through Threads. This allows conversational agents to remember context across multiple turns without manual state tracking.

Can I use OpenAI vector stores for retrieval-augmented generation with my own documents?▼

Yes, implement Retrieval-Augmented Generation using File Search and vector stores. You can upload your own documents to query against, supporting up to 10,000 files for accurate document-based answers.

How does code execution and data analysis work within an AI conversational agent?▼

Code execution within an AI conversational agent uses the Code Interpreter tool to run Python code, process data, and generate visual charts directly inside the conversation flow for dynamic analysis.

How do I connect external APIs to an AI assistant using function calling?▼

Connect external APIs to an AI assistant using function calling integrations. This extends the agent's capabilities by allowing it to trigger custom tools and interact with external services during conversations.

Does the OpenAI Assistants API support maintaining conversation history across multiple turns?▼

Yes, the OpenAI Assistants API supports maintaining conversation history across multiple turns using Threads. This handles complex conversational flows and context retention natively without manual session management.

What are the limitations of using vector stores for document Q&A with OpenAI assistants?▼

Vector stores for document Q&A support up to 10,000 files. While suitable for product documentation and troubleshooting, exceeding this limit or processing unsupported file types requires alternative data processing workflows.

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