Developer Onboarding

Who this page is for

Start here if you want to connect an application, script, AI coding tool, or OpenAI-compatible client to Skypool Token. After reading this guide, you should be able to create a Consumer API Key and complete your first model call through the unified OpenAI-compatible API.

The caller-side flow for Skypool Token is simple:

• Use one unified baseURL
• Use a Consumer API Key as the Bearer Token
• Select a platform model with the request body's model field
• Use the OpenAI-compatible /v1/chat/completions endpoint for regular chat, streaming output, tool calls, and multimodal input
• Review usage, status, failure reasons, and billing records in the console

API entry point

For production, set your OpenAI-compatible client's baseURL to:

https://a.skypool.xyz/v1

The full chat endpoint is:

https://a.skypool.xyz/v1/chat/completions

All OpenAI-compatible requests should carry the key in the request headers:

Authorization: Bearer <consumer_api_key>

Do not put the API Key in URLs, logs, public frontend code, or configuration files that users can download.

Step 1: Create a Consumer API Key

Log in to the Skypool Token console, open the Consumer-side API Key page, and click Create API Key. After creation succeeds, the page displays the full key. Consumer keys usually start with stc-.

We recommend splitting keys by application or environment, for example:

Step 2: Choose a model

View currently available models on the Models page or in the usage examples in the console.

You can also read the model list through the OpenAI-compatible API:

https://a.skypool.xyz/v1/models

Context length, pricing, tool-calling support, and multimodal capabilities may vary by model. Before connecting a production application, we recommend confirming the target model's response structure, latency, and failure semantics in the console or with a test script.

Step 3: Make your first request

The following is a minimal non-streaming request. Replace <consumer_api_key> with your Consumer API Key, and change model to the model you want to use.

For an even simpler test path, you can try it directly in Skypool Playground.

curl -X POST "https://a.skypool.xyz/v1/chat/completions" \  -H "Authorization: Bearer <consumer_api_key>" \  -H "Content-Type: application/json" \  --data-raw '{    "model": "gemma4:26b",    "messages": [      {        "role": "user",        "content": "Hello, introduce Skypool Token in one sentence."      }    ],    "max_tokens": 128,    "stream": false  }'

If the response contains choices[0].message.content, your key, endpoint, and model are working.

Step 4: Enable streaming output

For interactive scenarios such as chat, agents, and AI coding tools, streaming output is recommended. Use stream: true for streaming requests, and include stream_options.include_usage: true so the final frame can return real usage.

curl -N -X POST "https://a.skypool.xyz/v1/chat/completions" \  -H "Authorization: Bearer <consumer_api_key>" \  -H "Content-Type: application/json" \  --data-raw '{    "model": "gemma4:26b",    "messages": [      {        "role": "user",        "content": "Give me a minimal TypeScript HTTP client example."      }    ],    "max_tokens": 512,    "stream": true,    "stream_options": {      "include_usage": true    }  }'

Streaming responses follow the OpenAI-compatible SSE format: each event starts with data:, and a normal completion returns data: [DONE]. Clients should handle incremental delta.content, tool-call deltas, the final usage frame, and mid-stream error events.

Use the OpenAI SDK

Any OpenAI SDK or compatible client that supports a custom baseURL can connect directly to Skypool Token.

The example below supports switching between TypeScript and Python in the same code block and copying the code for the current language:

import OpenAI from "openai"; const client = new OpenAI({  apiKey: process.env.SKYPOOL_API_KEY,  baseURL: "https://a.skypool.xyz/v1",}); const completion = await client.chat.completions.create({  model: "gemma4:26b",  messages: [    {      role: "user",      content: "Explain the benefit of an OpenAI-compatible API in one sentence.",    },  ],  max_tokens: 128,}); console.log(completion.choices[0]?.message?.content);

Connect AI coding tools

AI coding tools usually need only three pieces of information:

Different tools use slightly different names for endpoint fields. Some tools ask for a baseURL, while others ask for the full chat completions address. Check the tool's field descriptions before configuring it:

• If the field is named baseURL, Base URL, or OpenAI API Base, enter https://a.skypool.xyz/v1
• If the field is named endpoint, API Endpoint, or API URL, and the example includes /chat/completions, enter https://a.skypool.xyz/v1/chat/completions

For common tool integrations, see:

• WorkBuddy integration
• OpenCode integration
• Cline integration
• Dify integration
• LiteLLM integration
• Vercel AI SDK integration

Request parameter recommendations

Review activity records

After a request completes, return to the Activity page in the Consumer console. You can review request time, model, status, Token usage, failure reason, and billing information there.

If you are debugging a third-party tool, first use curl or Skypool Playground to verify the same key and model, then migrate the same parameters into the tool configuration. This helps you quickly tell whether the issue is on the platform call path or in the tool-side configuration.

Common errors

Minimum onboarding checklist

1. Log in to the console and create a Consumer API Key
2. Choose a model ID from the Models page or /v1/models
3. Set your OpenAI-compatible client's baseURL to https://a.skypool.xyz/v1
4. Carry the API Key as a Bearer Token
5. Verify the basic call with a non-streaming curl request first
6. Then enable streaming output and tool calls
7. Check status, usage, and failure reasons in activity records