Bootstrap

POST /v1/ai-visibility/:appId/bootstrap

1. Reads your app metadata (title, subtitle, description, primary genre) and a sample of the keywords you already rank for.
2. Generates intents — 8–12 user goals your app addresses, written in the language a real user would use when asking an AI assistant.
3. Generates prompts per intent — 5–8 user-style queries spread across different styles (problem-led, branded, comparison, …).
4. Queues the first scan automatically so fresh data appears within ~10 minutes.

Bootstrap is idempotent. Re-running it later (after editing your app’s title, for example) only adds new intents the LLM proposes — it never deletes intents you’ve edited or added manually.

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Path parameters

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Body

{
  "country": "us",
  "language": "en"
}

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Response

{
  "data": {
    "taskRunId": "run_a1b2c3d4..."
  }
}

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What happens after the call

# 1. Confirm intents were generated
curl "https://api.appeeky.com/v1/ai-visibility/1234567890/intents?country=us" \
  -H "X-API-Key: YOUR_API_KEY"

# 2. After a few minutes, the overview gauge will populate
curl "https://api.appeeky.com/v1/ai-visibility/1234567890/overview?country=us&model=chatgpt" \
  -H "X-API-Key: YOUR_API_KEY"

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When to re-run bootstrap

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Code examples

curl -X POST "https://api.appeeky.com/v1/ai-visibility/1234567890/bootstrap" \
  -H "X-API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "country": "us", "language": "en" }'

const res = await fetch(
  "https://api.appeeky.com/v1/ai-visibility/1234567890/bootstrap",
  {
    method: "POST",
    headers: {
      "X-API-Key": "YOUR_API_KEY",
      "Content-Type": "application/json",
    },
    body: JSON.stringify({ country: "us", language: "en" }),
  }
);
const { data } = await res.json();
console.log("Bootstrap queued:", data.taskRunId);

// Poll the intents endpoint after ~30s
setTimeout(async () => {
  const r = await fetch(
    "https://api.appeeky.com/v1/ai-visibility/1234567890/intents?country=us",
    { headers: { "X-API-Key": "YOUR_API_KEY" } }
  );
  console.log(await r.json());
}, 30_000);

import requests

r = requests.post(
  "https://api.appeeky.com/v1/ai-visibility/1234567890/bootstrap",
  headers={"X-API-Key": "YOUR_API_KEY"},
  json={"country": "us", "language": "en"},
)
print("Bootstrap queued:", r.json()["data"]["taskRunId"])

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Credits

• The bootstrap call itself is free (intent + prompt generation runs on Appeeky’s account, not yours).
• The initial scan that runs immediately afterwards is metered like any other scheduled scan — see the Scan & Settings cost table. For an 8-intent × 6-prompt × 1-model (chatgpt) setup that’s ~432 credits up front.

• Tier gate: bootstrap requires the Indie plan or higher. Free-plan calls return 403 TIER_LIMIT_EXCEEDED.
• Quota gate: when the AI Visibility bucket is empty, bootstrap returns 429 AI_VISIBILITY_QUOTA_EXCEEDED instead of queuing intents+prompts the user can’t measure.

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Errors

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See also

• Overview — what AI Visibility is
• Overview endpoint — read the gauge after bootstrap completes
• Intents — view, edit, or add intents the LLM generated
• Scan & Settings — control the daily cadence