For AI

Everything an AI coding assistant needs to build a CrispHive integration — a ready-to-paste prompt, machine-readable resources, and the key facts about the API in one place.

Install with AI

Paste this prompt into your AI coding assistant to bootstrap an integration:

Read the CrispHive backend integration skill at
https://api.crisphive.com/developers/SKILL.md and the OpenAPI spec at
https://api.crisphive.com/developers/openapi.json.

Then implement a client for my backend that:
1. Authenticates with an API key as a Bearer token (chsk_test_… for sandbox)
2. Creates a customer and a job request
3. Keeps job requests in sync by polling GET /v1/job-requests/changes
   with the next_since cursor

Every response uses one envelope shape — { error_code, message, errors, data } — so generated clients can share a single response parser.

Machine-readable resources

Both files are served by the API itself, so they always match the deployed version — point your assistant straight at these URLs instead of copying docs pages into its context.

Resource	What it contains
`SKILL.md`	A condensed integration guide written for agents: authentication, the response envelope, core booking flows, and common pitfalls.
`openapi.json`	The full OpenAPI spec — every endpoint, request/response schema, and error code. Use it to generate typed clients.

Key facts for your assistant

The base URL is https://api.crisphive.com/v1 — sandbox and live share the same paths; the environment is selected by the key prefix (chsk_test_… vs chsk_live_…).
Authenticate every request with Authorization: Bearer <api key>. Keys don’t expire and carry full access — keep them server-side.
An error_code of 0 means success; anything else is an error, and validation failures list per-field details in errors.
Mirror data by polling GET /v1/job-requests/changes with the returned next_since cursor instead of re-listing resources.
Webhooks are still in preview — build reliable sync on the change feed for now.

Tips for better results

Have the assistant read SKILL.md first — it is small enough to fit in context and answers most integration questions without the full spec.
Generate request/response types from openapi.json rather than letting the model guess field names.
Develop against a sandbox key (chsk_test_…) and switch to live only after the flows work end to end.
When debugging, assert on error_code — not the HTTP status alone.