{
  "ocm": "1",
  "id": "jeremylongshore-tons-of-skills-marketplace-runway-rate-limits",
  "kind": "skill",
  "name": "runway-rate-limits",
  "description": "Runway rate limits — AI video generation and creative AI platform. Use when working with Runway for video generation, image editing, or creative AI. Trigger with phrases like \"runway rate limits\", \"runway-rate-limits\", \"AI video generation\".",
  "publisher": "jeremylongshore",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "creative"
    ],
    "tags": [
      "skill-md",
      "saas",
      "runway",
      "ai",
      "video-generation",
      "creative",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Runway rate limits — AI video generation and creative AI platform. Use when working with Runway for video generation, image editing, or creative AI. Trigger with phrases like \"runway rate limits\", \"runway-rate-limits\", \"AI video generation\"."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/jeremylongshore/tons-of-skills-marketplace",
      "path": "skills/.curated/runway-rate-limits/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/jeremylongshore/tons-of-skills-marketplace/blob/HEAD/skills/.curated/runway-rate-limits/SKILL.md",
      "key": "jeremylongshore/tons-of-skills-marketplace/skills/.curated/runway-rate-limits/SKILL.md"
    },
    "compatibility": "Designed for Claude Code",
    "allowed_tools": [
      "Read,",
      "Write,",
      "Edit,",
      "Bash(pip:*),",
      "Bash(npm:*),",
      "Bash(curl:*),",
      "Grep"
    ],
    "license": "MIT"
  },
  "instructions": "# Runway Rate Limits\n\n## Overview\n\nImplementation patterns for Runway rate limits — AI video generation platform.\n\n## Prerequisites\n\n- Completed `runway-install-auth` setup\n\n## Instructions\n\n### Step 1: SDK Pattern\n\n```python\nfrom runwayml import RunwayML\n\nclient = RunwayML()\n\ntask = client.image_to_video.create(\n    model='gen3a_turbo',\n    prompt_text='A serene lake at dawn, mist rising, birds flying',\n    duration=5,\n)\nresult = task.wait_for_task_output()\nif result.status == 'SUCCEEDED':\n    print(f\"Video: {result.output[0]}\")\n```\n\n## Output\n\n- Runway integration for rate limits\n\n## Error H",
  "cost": {
    "context_tokens": 262
  }
}