Build stateful chatbots with OpenAI Assistants API v2, including Code Interpreter, File Search (10k files), and Function Calling.
Works with
Three core tools: Code Interpreter for Python execution and file processing, File Search for semantic RAG with vector stores (10,000 files max), and Function Calling for custom tool integration
Manages four main objects—Assistants (configured AI with instructions), Threads (persistent conversation containers), Messages (with file attachments), and Runs (async
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionopenai-assistantsExecute the skills CLI command in your project's root directory to begin installation:
Fetches openai-assistants from jezweb/claude-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate openai-assistants. Access via /openai-assistants in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Status: Production Ready (⚠️ Deprecated - Sunset August 26, 2026) Package: [email protected] Last Updated: 2026-01-21 v1 Deprecated: December 18, 2024 v2 Sunset: August 26, 2026 (migrate to Responses API)
OpenAI is deprecating Assistants API in favor of Responses API.
Timeline: v1 deprecated Dec 18, 2024 | v2 sunset August 26, 2026
Use this skill if: Maintaining legacy apps or migrating existing code (12-18 month window)
Don't use if: Starting new projects (use openai-responses skill instead)
Migration: See references/migration-to-responses.md
npm install [email protected]
import OpenAI from 'openai';
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
// 1. Create assistant
const assistant = await openai.beta.assistants.create({
name: "Math Tutor",
instructions: "You are a math tutor. Use code interpreter for calculations.",
tools: [{ type: "code_interpreter" }],
model: "gpt-5",
});
// 2. Create thread
const thread = await openai.beta.threads.create();
// 3. Add message
await openai.beta.threads.messages.create(thread.id, {
role: "user",
content: "Solve: 3x + 11 = 14",
});
// 4. Run assistant
const run = await openai.beta.threads.runs.create(thread.id, {
assistant_id: assistant.id,
});
// 5. Poll for completion
let status = await openai.beta.threads.runs.retrieve(thread.id, run.id);
while (status.status !== 'completed') {
await new Promise(r => setTimeout(r, 1000));
status = await openai.beta.threads.runs.retrieve(thread.id, run.id);
}
// 6. Get response
const messages = await openai.beta.threads.messages.list(thread.id);
console.log(messages.data[0].content[0].text.value);
Four Main Objects:
const assistant = await openai.beta.assistants.create({
model: "gpt-5",
instructions: "System prompt (max 256k chars in v2)",
tools: [{ type: "code_interpreter" }, { type: "file_search" }],
tool_resources: { file_search: { vector_store_ids: ["vs_123"] } },
});
Key Limits: 256k instruction chars (v2), 128 tools max, 16 metadata pairs
// Create thread with messages
const thread = await openai.beta.threads.create({
messages: [{ role: "user", content: "Hello" }],
});
// Add message with attachments
await openai.beta.threads.messages.create(thread.id, {
role: "user",
content: "Analyze this",
attachments: [{ file_id: "file_123", tools: [{ type: "code_interpreter" }] }],
});
// List messages
const msgs = await openai.beta.threads.messages.list(thread.id);
Key Limits: 100k messages per thread
// Create run with optional overrides
const run = await openai.beta.threads.runs.create(thread.id, {
assistant_id: "asst_123",
additional_messages: [{ role: "user", content: "Question" }],
max_prompt_tokens: 1000,
max_completion_tokens: 500,
});
// Poll until complete
let status = await openai.beta.threads.runs.retrieve(thread.id, run.id);
while (['queued', 'in_progress'].includes(status.status)) {
await new Promise(r => setTimeout(r, 1000));
status = await openai.beta.threads.runs.retrieve(thread.id, run.id);
}
Run States: queued → in_progress → requires_action (function calling) / completed / failed / cancelled / expired (10 min max)
const stream = await openai.beta.threads.runs.stream(thread.id, { assistant_id });
for await (const event of stream) {
if (event.event === 'thread.message.delta') {
process.stdout.write(event.data.delta.content?.[0]?.text?.value || '');
}
}
Key Events: thread.run.created, thread.message.delta (streaming co
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
jezweb/claude-skills
jezweb/claude-skills
jezweb/claude-skills
davila7/claude-code-templates
intellectronica/agent-skills
am-will/codex-skills
openai-assistants reduced setup friction for our internal harness; good balance of opinion and flexibility.
openai-assistants is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: openai-assistants is focused, and the summary matches what you get after install.
We added openai-assistants from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: openai-assistants is focused, and the summary matches what you get after install.
I recommend openai-assistants for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added openai-assistants from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
openai-assistants fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
openai-assistants has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in openai-assistants — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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