STAPI

{
  "service_type": "platform",
  "base_url": "http://stapi.co",
  "auth_method": "none",
  "auth_config": {},
  "endpoints": [],
  "pricing_model": {"type": "free", "details": {}},
  "rate_limits": {},
  "capabilities": ["Star Trek data retrieval", "Search and filtering", "GraphQL API"],
  "raw_analysis": "STAPI is a free, community-driven, open-source API that provides structured information about the Star Trek universe. It is primarily aimed at developers building Star Trek-related applications, fan sites, or educational tools. The platform is relatively mature, having been active since around 2017, with a documented GraphQL endpoint and a REST API (though the REST version is deprecated). It offers comprehensive data on characters, episodes, series, movies, and more, with fields for images, relationships, and metadata. The API is open and requires no authentication, making it accessible for quick integration. However, there is no official SLA or rate limit documentation, and the data is based on fan contributions, so accuracy may vary. STAPI does not offer native integrations, but being a standard API, it can be used with any programming language. The platform is free to use, with no premium tier, and is maintained by a small team of volunteers."
}

2/3 tests passed

```json
{
  "overall": 62,
  "dimensions": {
    "token_efficiency": 8.0,
    "first_try_success": 7.0,
    "response_parseability": 9.0,
    "error_clarity": 5.0,
    "doc_quality": 5.0,
    "auth_simplicity": 10.0,
    "latency": 8.0,
    "consistency": 6.0
  },
  "pricing_normalized": {
    "type": "free",
    "note": "No pricing details available, API appears free to use"
  },
  "issues": [
    "No llms.txt endpoint (404) — reduces agent discoverability",
    "Missing security headers — potential trust concern",
    "No explicit error documentation or limitation details in docs preview",
    "No obvious rate limit or usage policy documentation found"
  ],
  "recommendations": [
    "Add /llms.txt file with API overview, endpoints, and usage examples for AI agents",
    "Publish rate limits and error response formats clearly",
    "Document all query parameters and filtering capabilities",
    "Consider adding structured API reference (OpenAPI/Swagger) documentation"
  ]
}
```