llm-call

Call configured LLM providers directly through Anthropic, OpenAI, or Gemini API protocols.

1.3k|142|Updated Jun 1, 2026
One-click install
npx skills add https://github.com/MiniMax-AI/minimax-code --skill llm-call-minimax-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: llm-call
Source: https://github.com/MiniMax-AI/minimax-code/tree/main/packages/local-runtime/assets/skills/llm-call
Command: npx skills add https://github.com/MiniMax-AI/minimax-code --skill llm-call-minimax-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires httpx, pyyaml, and includes scripts (resource) components.

What problem does it solve? Testing prompts or comparing models normally requires switching between provider SDKs and writing boilerplate code for each API. This Skill lets you send a raw prompt to any model configured in your MiniMax Code config.yaml with a single command, without touching provider-specific request formats. ## Core Features & Use Cases - Multi-Protocol Support: Automatically maps providers to the correct API protocol — Anthropic Messages, OpenAI Chat Completions, or Gemini generateContent — based on the provider's npm field in config.yaml. - Model Discovery and Selection: List all configured models with --list, call a specific provider/model reference, or fall back to the configured defaultModel. - Streaming and Parameter Control: Supports streaming output, system prompts, temperature, max tokens, custom timeouts, and JSON output for scripting. - Use Case: Compare how gemini/gemini-2.5-pro and an OpenAI-compatible model answer the same prompt by running the script twice with different --model flags, then review the outputs side by side. ## Quick Start Ask the agent to call a configured model with your prompt, for example: run the llm-call script with model gemini/gemini-2.5-pro and the prompt "Summarize this document".

Frequently Asked Questions about llm-call

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

FAQPage Schema
How do I call an LLM API directly from the command line?

Run the llm_call.py script with --model in provider/model format and --prompt with your text. It reads credentials and base URLs from config.yaml and prints the model's response, with optional --stream for streaming output.

How do I list available models configured in config.yaml?

Run the script with the --list flag to print every configured model as a provider/model reference along with its display name. The configured defaultModel is marked, and --json outputs the list as structured JSON.

Which LLM API protocols does the script support?

The script supports three protocols mapped from the provider's npm field: Anthropic Messages for @ai-sdk/anthropic, OpenAI Chat Completions for @ai-sdk/openai, and Gemini generateContent for @ai-sdk/google. Unknown providers default to chat completions.

Can I use the script on Windows without python3 installed?

Yes, use the py -3 launcher on Windows since python3 is not part of a default Windows install. On macOS and Linux, python3 is preferred, or python if it points to Python 3.

Why does the LLM call fail with a provider or config error?

Failures occur when config.yaml is missing, the requested provider or model is not configured, or credentials are absent. The script reports the specific missing provider or HTTP error and does not silently retry with another model.