Kimi K3.1 Pro

curl -X POST https://superpowers.tools/v1/run \
  -H 'Authorization: Bearer $SP_KEY' \
  -d '{"tool":"openrouter.moonshotai-kimi-k3.1-pro","input":{"prompt":"Explain MCP in one sentence."},"idempotency_key":"example-request-1"}'

{
  "type": "object",
  "properties": {
    "prompt": {
      "type": "string"
    },
    "system": {
      "type": "string"
    },
    "messages": {
      "type": "array",
      "description": "OpenAI-style messages; overrides prompt. content is a string or an array of parts: { type: \"text\", text } and, for images, { type: \"image_url\", image_url: { url } } with an https URL or a base64 data:image/png|jpeg|webp|gif URL. At most 5 images per call (more is refused with 400), and the whole input must stay under 1 MB, so pass large images by URL. Vision is supported for Google Gemini models only for now: Gemini 3 models (e.g. openrouter.google-gemini-3.1-flash-lite), priced at up to 2,240 input tokens per image; other models refuse images because their per-image cost cannot be bounded."
    },
    "max_tokens": {
      "type": "integer",
      "default": 1024
    },
    "temperature": {
      "type": "number"
    },
    "reasoning_effort": {
      "type": "string",
      "description": "Reasoning models only. Defaults to the lowest effort the model accepts; \"none\" turns reasoning off where the model allows it."
    },
    "reasoning_max_tokens": {
      "type": "integer",
      "description": "OpenRouter reasoning models only. Output tokens reserved for thinking on top of max_tokens (default 4096 where the model accepts a thinking budget, else 8192; at the lowest reasoning effort, 8x max_tokens when that is smaller, at least 1024); priced into the reservation."
    },
    "response_format": {
      "type": "object",
      "description": "Structured output, OpenAI format: {type: 'json_schema', json_schema: {name, schema, strict: true}} or {type: 'json_object'}. The answer comes back as text and, parsed, as parsed. OpenAI models take both; OpenRouter models need the structured-outputs tag for json_schema."
    },
    "tools": {
      "type": "array",
      "maxItems": 128,
      "description": "Function calling, OpenAI format: [{type: 'function', function: {name, description, parameters (JSON Schema), strict}}]. Calls come back in tool_calls; send results as {role: 'tool', tool_call_id, content} messages after the assistant message with tool_calls. OpenRouter models need the tools tag."
    },
    "tool_choice": {
      "description": "auto, none, required, or {type: 'function', function: {name}}"
    },
    "parallel_tool_calls": {
      "type": "boolean"
    }
  }
}

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string"
    },
    "model": {
      "type": "string"
    },
    "input_tokens": {
      "type": "integer"
    },
    "output_tokens": {
      "type": "integer"
    },
    "finish_reason": {
      "type": "string"
    },
    "tool_calls": {
      "type": "array"
    },
    "parsed": {
      "type": "object"
    }
  },
  "required": [
    "text",
    "model",
    "input_tokens",
    "output_tokens",
    "finish_reason",
    "tool_calls",
    "parsed"
  ]
}