# Nativecheck

> Native-speaker verification for machine (LLM) translations. Agents first: quote, get human approval, order, come back later, collect.

Nativecheck = native speakers verify machine translations; reviews take minutes to hours, so it is asynchronous. 1) Collect ALL texts you need checked and POST /api/v1/quotes once (requested_by: "agent", agent: your name; items: target_lang + content as text, html or a JSON object; optional ref, source, context, doubt 0-100, doubt_note). 2) Show summary_for_human (price range + ETA) to your human and ask for approval. 3) POST /api/v1/orders {quote_id} with an Idempotency-Key header. Save order_id + check_after in memory, tell the human the ETA, and follow wait_plan: start a long-running background task/timer that waits until check_after, then polls GET /api/v1/orders/{id} every 60 s. 4) When ready=true, GET /api/v1/orders/{id}/delivery and replace your texts by ref. 5) POST /api/v1/orders/{id}/ack. The human also gets an in-app/push notification when ready. Keep placeholders like {name}, %s and ⟦1⟧ unchanged. Prices are coins (1 coin = $0.01).

Auth: Authorization: Bearer <API key> (created by the human at https://nativecheck.data-clerk.com/wallet).

## API
- [Full guide for agents (markdown)](https://nativecheck.data-clerk.com/llms-full.txt) · [OpenAPI](https://nativecheck.data-clerk.com/openapi.json) · [MCP server card](https://nativecheck.data-clerk.com/.well-known/mcp.json) · [Docs](https://nativecheck.data-clerk.com/docs)
- POST https://nativecheck.data-clerk.com/api/v1/quotes · POST https://nativecheck.data-clerk.com/api/v1/orders · GET https://nativecheck.data-clerk.com/api/v1/orders/{id} · GET https://nativecheck.data-clerk.com/api/v1/orders/{id}/delivery · POST https://nativecheck.data-clerk.com/api/v1/orders/{id}/ack · GET https://nativecheck.data-clerk.com/api/v1/wallet · GET https://nativecheck.data-clerk.com/api/v1/languages

## MCP
- Streamable HTTP: https://nativecheck.data-clerk.com/mcp (same Bearer key). Tools: quote_review, place_order, check_order, collect_order, ack_order, balance, languages.
## Related

- [Coffee Types](https://coffeetypes.data-clerk.com/): visual guide to coffee drinks in 29 languages ([llms.txt](https://coffeetypes.data-clerk.com/llms.txt))
- [Tea Types](https://teatypes.data-clerk.com/): visual guide to teas with brewing data in 18 languages ([llms.txt](https://teatypes.data-clerk.com/llms.txt))
- [Data Clerk](https://data-clerk.com/): the studio behind Nativecheck ([llms.txt](https://data-clerk.com/llms.txt))