Endpoints

{
  "service_type": "platform",
  "base_url": "https://tokenmetrics.com",
  "auth_method": "unknown",
  "auth_config": {},
  "endpoints": [],
  "pricing_model": {
    "type": "unknown",
    "details": {}
  },
  "rate_limits": {},
  "capabilities": [
    "crypto analytics",
    "AI-powered crypto research",
    "market data",
    "token ratings and grades",
    "quantitative crypto signals",
    "portfolio insights"
  ],
  "raw_analysis": "Token Metrics (tokenmetrics.com) is a crypto analytics and research platform that provides AI-driven market insights, token ratings, price predictions, and quantitative signals for cryptocurrency investors and traders. The provided content is a client-side rendered React Router (SPA mode) shell, so no actual page content, documentation, or API surface is visible. This indicates the site is a JavaScript-rendered single-page application with no server-side HTML for crawlers to parse. Key observations: (1) The page includes Google Tag Manager (G-WW36F3TJ75) and Intercom chat integration, suggesting an active SaaS product with customer support. (2) The URL was described as an 'API provider', and Token Metrics is publicly known to offer a REST API (api.tokenmetrics.com) with endpoints for tokens, market metrics, trading signals, and price data, typically authenticated via an API key—though none of this is confirmed from the fetched content itself. (3) Because the shell provides no links to documentation, pricing tiers, or auth flows, the auth method, pricing model, and specific endpoints cannot be verified from this snapshot alone. (4) The platform is vertically focused on crypto/Web3 analytics, targeting retail and institutional investors, traders, and developers who want to integrate crypto signals into their own applications. (5) Maturity appears high given the dedicated branding, analytics, support tooling, and SPA infrastructure, but concrete maturity and integration details would require fetching their API documentation (e.g., /api or a docs subdomain) directly. No endpoints, auth mechanisms, or rate limits can be confirmed from the given content."
}

3/3 tests passed

{
  "overall": 62,
  "dimensions": {
    "token_efficiency": 8.0,
    "first_try_success": 6.0,
    "response_parseability": 5.0,
    "error_clarity": 4.0,
    "doc_quality": 5.0,
    "auth_simplicity": 6.0,
    "latency": 10.0,
    "consistency": 7.0
  },
  "pricing_normalized": {
    "type": "unknown",
    "notes": "No public pricing details detected in analysis payload; users must visit site to determine tiers."
  },
  "issues": [
    "No llms.txt or agent-oriented discovery file (llms_txt probe returned the app HTML shell instead of a machine-readable doc)",
    "Pricing model undisclosed in structured form — agents cannot easily quote cost or recommend tier",
    "No public API documentation surfaced in checks; response_parseability limited to web UI",
    "Documentation quality unknown; no getting-started/help docs preview retrieved",
    "Auth flow not confirmed (likely standard email/OAuth signup) — no magic link or Notlogin-style agent-friendly onboarding observed"
  ],
  "recommendations": [
    "Publish an llms.txt and/or AI-readable sitemap to aid agent discovery and reduce token cost when describing the platform",
    "Expose a public REST/GraphQL API with documented endpoints for market data and token grades to improve parseability",
    "Add a structured pricing page (JSON-LD or plain-text) so agents can surface accurate cost info",
    "Provide clear limitation docs (e.g., data coverage, refresh cadence, rate limits) to improve error_clarity",
    "Consider magic-link or Notlogin-compatible auth to streamline agent-assisted onboarding"
  ]
}