Using an AI agent

# Every endpoint on one platform
curl "https://api.insightsocial.app/v1/endpoints?platform=tiktok"

{
  "path": "/v1/tiktok/profile",
  "method": "GET",
  "platform": "tiktok",
  "description": "Returns a TikTok account's public profile: display name, bio, follower count ...",
  "credits": 20,
  "paginates": false,
  "cache_ttl_seconds": 86400,
  "params": [
    { "name": "handle", "required": false, "in": "query", "type": "string",
      "example": "charlidamelio", "one_of_group": "handle|user_id" },
    { "name": "user_id", "required": false, "in": "query", "type": "string",
      "one_of_group": "handle|user_id" }
  ],
  "available": true
}

export INSIGHTSOCIAL_API_KEY=isk_live_...

Set up the InsightSocial API in this project and make a first successful call.

Facts you can rely on:
- Base URL: https://api.insightsocial.app/v1
- Auth: send the header `x-api-key: $INSIGHTSOCIAL_API_KEY` on every request. Read the key from
  the environment. Never print it, put it in a URL, or commit it. Authorization: Bearer is refused.
- All data endpoints are GET with query parameters.
- Success responses look like: { success: true, platform, endpoint, data, pagination?,
  credits_used, credits_remaining, request_id, cached, idempotent_replay, charge_reason, free_call }.
  List responses add pagination { next_cursor, has_more }.
- Error responses look like: { success: false, error: { type, message }, request_id,
  credits_used, credits_remaining }.
- Prices are per endpoint, in credits. Failed calls, empty results and dry_run=1 calls are
  never charged. Repeating the exact same call within the endpoint's cache_ttl_seconds is free.

Before writing any call, read the catalogue instead of guessing paths or parameters.
It is free and needs no key:
  GET https://api.insightsocial.app/v1/endpoints
  GET https://api.insightsocial.app/v1/endpoints?platform=<platform>
Use only endpoints where available is true, only parameters listed for that endpoint,
and tell me the price (credits, or min-max for metered) before any call over 100 credits.

Then, in order:
1. Verify the key with GET https://api.insightsocial.app/v1/credits (free) and print
   credits_remaining.
2. Call GET https://api.insightsocial.app/v1/tiktok/profile?handle=khaby.lame and print
   data.author.followers and credits_used.
3. Read the same kind of account on instagram/profile (handle=natgeo), youtube/channel
   (handle=mkbhd) and twitter/profile (handle=nasa). Print one line per platform.
4. Pick one list endpoint from the catalogue whose paginates is true, and read two pages by
   sending pagination.next_cursor back as ?cursor= while has_more is true. Send cursor values
   back unchanged.

Rules:
- Check `success` before using `data`. Branch on error.type, never on the message text.
- Retry only on HTTP 429, HTTP 503, IDEMPOTENCY_IN_PROGRESS and INTERNAL_ERROR. Wait for the
  Retry-After header when present, then back off with jitter. Never retry other 4xx errors.
- On INSUFFICIENT_CREDITS, stop and tell me. Do not retry.
- Stay under 60 requests per minute and 10 requests in flight.
- Stop and ask me before spending more than 1,000 credits in total.

curl "https://api.insightsocial.app/v1/credits" \
  -H "x-api-key: $INSIGHTSOCIAL_API_KEY"

import os
import requests

KEY = os.environ["INSIGHTSOCIAL_API_KEY"]
BASE = "https://api.insightsocial.app/v1"

# Give the model this catalogue once, as reference text or a second tool.
CATALOGUE = requests.get(f"{BASE}/endpoints", timeout=30).json()

def insightsocial_get(path: str, params: dict) -> dict:
    """Tool: call one InsightSocial endpoint, e.g. path='tiktok/profile'."""
    res = requests.get(f"{BASE}/{path.removeprefix('/v1/').lstrip('/')}",
                       params=params, headers={"x-api-key": KEY}, timeout=120)
    body = res.json()
    if not body["success"]:
        # Hand the model a short instruction, not a raw error envelope.
        retry = res.headers.get("Retry-After")
        return {"error": body["error"]["type"], "message": body["error"]["message"],
                "retry_after_seconds": retry}
    return {"data": body["data"], "pagination": body.get("pagination"),
            "credits_used": body["credits_used"],
            "credits_remaining": body["credits_remaining"]}