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API skill for AI agents

This page gives you a ready-made skill file that teaches an AI agent how to use the Spheron GPU API. Hand it to Claude or ChatGPT, and the agent understands the full deployment flow: which endpoint to call, in what order, how each parameter works, and how to handle errors, provider rules, and instance lifecycles.

The skill is one self-contained Markdown file. It works as a Claude Agent Skill, a ChatGPT custom GPT instruction set, or a system prompt for any LLM that can make HTTP requests.

Download spheron-gpu-api-skill.md

What the skill teaches the agent

  • The full deploy flow: providers, GPU offers, SSH keys, deployment, status polling, termination.
  • A decision framework that maps a user request to the correct endpoint and call order.
  • How every deployment parameter works, including which fields must all come from the same GPU offer.
  • Provider-specific rules for volumes, instance types, and Kubernetes add-ons.
  • Status values, the deployment lifecycle, error codes, and rate limits.
  • That an API key is required, and that access comes from the dashboard or by contacting info@spheron.ai.

Prerequisites

  • A Spheron API key. Generate one from your dashboard settings. If you do not have API access yet, request it from info@spheron.ai.
  • An AI agent that can make HTTPS requests, or that you supply request output to manually.

Use the skill with Claude

Choose the option that matches how you run Claude.

Claude Code or the Claude Agent SDK

  1. Download spheron-gpu-api-skill.md.
  2. Create a skill folder and rename the file to SKILL.md inside it:
mkdir -p ~/.claude/skills/spheron-gpu-api
mv spheron-gpu-api-skill.md ~/.claude/skills/spheron-gpu-api/SKILL.md
  1. Start Claude Code. The skill loads automatically when your request matches its description (renting or managing GPUs on Spheron).
  2. Save your API key once on your local system so the agent reads it automatically on every run instead of asking again:
# Persist the key for future shells
echo 'export SPHERON_API_KEY="<your-api-key>"' >> ~/.zshrc

The skill instructs the agent to read SPHERON_API_KEY (or a local ~/.spheron/credentials file) before each authenticated call.

Claude apps and Projects

  1. Download the file.
  2. Add it to a Project's knowledge, or paste its contents into the custom instructions or the start of a conversation.
  3. Tell Claude your goal, for example: "Deploy a single H100 on Spheron and give me the SSH command." Provide your API key when asked.

Use the skill with ChatGPT

Custom GPT

  1. Open the GPT builder and go to Configure.
  2. Open spheron-gpu-api-skill.md, copy its full contents, and paste them into the Instructions field.
  3. Optionally enable Actions and import the API so the GPT can call endpoints directly. Add your API key as a Bearer token in the authentication settings.

Standard chat

  1. Paste the contents of the file as your first message, or save it as a custom instruction.
  2. Add your goal and your API key in the same conversation.

Use the skill with any LLM agent

The file is plain Markdown with no tool-specific syntax. Load it as the system prompt for any agent framework that can issue HTTPS requests to https://app.spheron.ai. The agent then follows the decision framework and parameter rules in the file.

Keep the skill current

The skill mirrors the API reference. When the API changes, download the file again so your agent uses the latest endpoints, parameters, and provider rules.

What's next

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