Kaggle

{
  "service_type": "platform",
  "base_url": "https://www.kaggle.com",
  "auth_method": "api_key",
  "auth_config": {
    "type": "api_key",
    "credentials": "username and API key (obtainable from Kaggle account settings)",
    "header": "Authorization: Bearer <api_key> or via HTTP basic auth (username:key) for public API endpoints"
  },
  "endpoints": [
    {
      "path": "/api/v1/datasets/list",
      "method": "GET",
      "description": "List datasets matching a query"
    },
    {
      "path": "/api/v1/datasets/view/{ownerSlug}/{datasetSlug}",
      "method": "GET",
      "description": "Get metadata for a specific dataset"
    },
    {
      "path": "/api/v1/datasets/download/{ownerSlug}/{datasetSlug}",
      "method": "GET",
      "description": "Download a dataset as a zip file"
    },
    {
      "path": "/api/v1/datasets/upload",
      "method": "POST",
      "description": "Upload a new dataset (multipart/form-data)"
    },
    {
      "path": "/api/v1/datasets/create",
      "method": "POST",
      "description": "Create a dataset from an existing file or URL"
    },
    {
      "path": "/api/v1/datasets/update",
      "method": "POST",
      "description": "Update an existing dataset"
    },
    {
      "path": "/api/v1/kernels/push",
      "method": "POST",
      "description": "Push a notebook (kernel) to Kaggle"
    },
    {
      "path": "/api/v1/kernels/pull",
      "method": "POST",
      "description": "Pull a notebook from Kaggle"
    },
    {
      "path": "/api/v1/kernels/list",
      "method": "GET",
      "description": "List kernels (notebooks) matching a query"
    },
    {
      "path": "/api/v1/kernels/output",
      "method": "GET",
      "description": "Get notebook output files"
    },
    {
      "path": "/api/v1/competitions/list",
      "method": "GET",
      "description": "List competitions"
    },
    {
      "path": "/api/v1/competitions/data/list/{competitionId}",
      "method": "GET",
      "description": "List files for a competition"
    },
    {
      "path": "/api/v1/competitions/data/download/{competitionId}/{fileName}",
      "method": "GET",
      "description": "Download a competition file"
    },
    {
      "path": "/api/v1/competitions/submissions/submit",
      "method": "POST",
      "description": "Submit to a competition"
    }
  ],
  "pricing_model": {
    "type": "freemium",
    "details": "Free tier offers access to public datasets, notebooks, competitions, and limited GPU hours per week. Paid subscription tier (Pro) provides increased GPU quota, more frequent API access, and priority support."
  },
  "rate_limits": {
    "general": "Rate limits are applied based on usage; free tier has lower limits, Pro tier has higher.",
    "recommended": "Avoid frequent polling; use webhooks or fetch on demand. Public API endpoints are rate-limited per user; see official docs for specifics."
  },
  "capabilities": [
    "Search and download public datasets",
    "Upload and manage datasets",
    "Create and run notebooks (kernels) in various languages (Python, R, SQL)",
    "Access competition data and submit predictions",
    "Use GPU/TPU resources for compute",
    "Integrate with Kaggle CLI and Python client library",
    "Collaborate with other data scientists via public/private kernels",
    "Use Kaggle's cloud-based environment for model training"
  ],
  "raw_analysis": "Kaggle is a well-established data science platform owned by Google. It provides a comprehensive REST API for programmatic access to datasets, competitions, and notebooks. The API is widely used by data scientists and machine learning practitioners for automating data retrieval, model training, and submission workflows. The platform is mature with a large ecosystem, including official Python and CLI clients. The API requires API key authentication, which is straightforward. Pricing is freemium, with a free tier that includes significant functionality. Rate limits exist but are typically sufficient for normal usage. Integrations include the ability to connect to Google Cloud Storage, BigQuery, and various MLOps tools. Overall, it is a top-tier platform for data science collaboration and competition."
}

2/3 tests passed

```json
{
  "overall": 54,
  "dimensions": {
    "token_efficiency": 6.0,
    "first_try_success": 4.0,
    "response_parseability": 7.0,
    "error_clarity": 5.0,
    "doc_quality": 6.0,
    "auth_simplicity": 3.0,
    "latency": 9.0,
    "consistency": 5.0
  },
  "pricing_normalized": {
    "free_tier": true,
    "paid_tier": "Pro subscription for more GPU hours and API access"
  },
  "issues": [
    "Requires Google account sign-in (no magic link or agent-friendly SSO)",
    "robots.txt returns 404 - not an error, but missing file may confuse automated tools",
    "No llms.txt file (though there is a /llms.txt that appeared in checks, it's unclear if it's official)",
    "Free tier has strict weekly GPU limits and slower API rate limits",
    "Authentication flow is legacy Google OAuth - no headless agent-friendly API key provisioning",
    "Docs focus on human-centric web interface rather than agent-first API usage"
  ],
  "recommendations": [
    "Add an API-key based authentication flow for programmatic access",
    "Publish a formal llms.txt with feature summaries and API endpoints",
    "Provide rate limit headers and clear error codes in API responses",
    "Add a dedicated getting-started guide for AI agents (not just humans)",
    "Improve error clarity for kernel/notebook submission failures"
  ]
}
```