GET /v1/usage#

Daily series of API request counts for your account, plus today/week/month summary. Same data the dashboard usage page reads — exposed programmatically so SDKs, billing automation, and monitoring tools don’t have to scrape HTML.

The endpoint aggregates across all your API keys (test + live) under your account. Use GET /v1/me to inspect a specific key’s recent rate-limit state.

Parameters#

Examples#

Response#

{
  "summary": {
    "tier": "free",
    "today": { "count": 142, "prev": 87, "delta": 63, "limit": 500, "windowStart": "2026-05-04", "windowEnd": "2026-05-04" },
    "week": { "count": 891, "prev": 612, "delta": 45, "limit": null, "windowStart": "2026-04-28", "windowEnd": "2026-05-04" },
    "month": { "count": 3422, "prev": 2891, "delta": 18, "limit": null, "windowStart": "2026-05-01", "windowEnd": "2026-05-04" }
  },
  "series": [
    { "day": "2026-04-28", "requests": 87, "errors": 0, "clientErrors": 2 },
    { "day": "2026-04-29", "requests": 124, "errors": 0, "clientErrors": 0 }
  ],
  "meta": {
    "from": "2026-04-28",
    "to": "2026-05-04",
    "days": 7,
    "requestId": "req_..."
  }
}

series[].errors is 5xx (our problem). series[].clientErrors is 4xx (your side — 401/429/400/422). Split deliberately so you can tell whose fault a spike is.

summary.*.delta is the percentage change from the previous equivalent window (today vs yesterday, this week vs last week, this month vs last month). null when the previous window had zero requests.

Performance#

• p50 (warm): ~50ms
• p95: <150ms for a 30-day window
• Last measured: 2026-05-07
• SLO: p95 < 500ms, error rate < 1%

See also#

• GET /v1/me — current key’s rate-limit state and tier
• Pricing — what limits and caps apply to each tier