# Botify Agent: AI Visibility Campaigns List

**ID:** `ai_visibility_campaigns_list`

List the AI Visibility campaigns configured on the current project.

List the AI Visibility campaigns configured on the current project: name, id, status, platforms, countries, and how prompts are sourced.

## Authentication

All endpoints require a **Bearer token** in the `Authorization` header.

```
Authorization: Bearer <your-token>
```

## Calling this agent

This agent supports the following processing modes:

| Mode | Type | Description |
|------|------|-------------|
| **Process** | Synchronous | Single-item processing. Best for real-time requests with immediate response. |
| **Batch Process** | Synchronous | Process multiple items in a single request for efficiency. |
| **Async Process** | Asynchronous | Single-item processing for long-running tasks that exceed timeout limits. |
| **Async Batch Process** | Asynchronous | Large-scale batch jobs with background processing. |

# Synchronous Processing

Synchronous calls block until the result is ready. Use these for quick operations where you need immediate results.

## Single Item Processing

Process a single input and receive the result immediately.

```
POST https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/process
```

### Request body

```json
{
  "item": {}
}
```

### Response

Returns a single processed item (HTTP 200).

### cURL example

```bash
curl -X POST "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/process" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "item": {}
}'
```

## Batch Processing

Process multiple inputs in a single synchronous request. More efficient than making individual calls. Items are processed concurrently on the server.

```
POST https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/batch_process
```

### Request body

```json
{
  "items": [
    {}
  ]
}
```

### Response

Returns an array of results. Each element is either a successful processed item (`"status": "success"`) or an error (`"status": "error"`).

### cURL example

```bash
curl -X POST "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/batch_process" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "items": [
    {}
  ]
}'
```

### When to use synchronous calls

- Processing completes within timeout limits (typically 30 seconds)
- You need immediate results for user-facing features
- Small to medium batch sizes (up to ~100 items)

# Asynchronous Processing

Asynchronous calls return immediately with a batch ID. You then poll for results using the `async_batches/` endpoints.

### Async processing flow

1. **Submit job** -- `POST` to `async_process` or `async_batch_process`
2. **Receive batch ID** -- response contains `batch_id`
3. **Poll status** -- `HEAD` request to check readiness (lightweight, no body)
4. **Get results** -- `GET` request to retrieve processed results

## Async Single Item

Submit a single item for background processing. Use the `/single` endpoint to retrieve the result.

```
POST https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_process
```

### Request body

```json
{
  "item": {}
}
```

### cURL example

```bash
# Step 1: Submit the job
curl -X POST "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_process" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "item": {}
}'

# Response: { "batch_id": "abc123" }

# Step 2: Check if batch is ready (HEAD request -- lightweight check)
curl -I -X HEAD "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_batches/abc123" \
  -H "Authorization: Bearer $TOKEN"
# Returns 200 if ready, 204 if still processing

# Step 3: Get the result (for single-item async)
curl -X GET "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_batches/abc123/single" \
  -H "Authorization: Bearer $TOKEN"
# Returns 200 with result, 202 if still processing, 404 if batch not found
```

## Async Batch Processing

Submit multiple items for background processing. The request body uses **JSONL** (newline-delimited JSON) format.

```
POST https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_batch_process
```

### Request body (JSONL, `Content-Type: text/plain`)

The first line contains `config` and `batch_config`. Each subsequent line is an item with a unique `id`.

```
{"config": {}, "batch_config": {}}
{"id": "item_1", "item": {}}
```

### Response

Returns a JSON object with `batch_id`, `status`, and a `Location` header.

### cURL example

```bash
# Step 1: Submit the batch job
curl -X POST "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_batch_process" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: text/plain" \
  -d '{"config": {}, "batch_config": {}}\n{"id": "item_1", "item": {}}'

# Response: { "batch_id": "xyz789" }

# Step 2: Check if batch is ready (HEAD request)
curl -I -X HEAD "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_batches/xyz789" \
  -H "Authorization: Bearer $TOKEN"
# Returns 200 if ready, 204 if still processing

# Step 3: Get all results
curl -X GET "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_batches/xyz789" \
  -H "Authorization: Bearer $TOKEN"
```

## Checking Batch Status

Use a lightweight `HEAD` request to check if your batch is ready without transferring data.

```
HEAD https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_batches/{batch_id}
```

```bash
curl -I -X HEAD "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_batches/{batch_id}" \
  -H "Authorization: Bearer $TOKEN"

# Response headers indicate status:
# HTTP/1.1 200 OK        -> Batch is complete, results ready
# HTTP/1.1 204 No Content -> Still processing
# HTTP/1.1 404 Not Found -> Batch does not exist
```

## Retrieving Results

Once the batch is ready, fetch results using the appropriate endpoint.

```bash
# For async_process (single item) -- use /single endpoint
curl -X GET "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_batches/{batch_id}/single" \
  -H "Authorization: Bearer $TOKEN"

# For async_batch_process (multiple items) -- use base endpoint
curl -X GET "https://agents.botify.com/{org}/{project}/ai_visibility_campaigns_list/async_batches/{batch_id}" \
  -H "Authorization: Bearer $TOKEN"
# Returns streaming JSONL where each line is a processed item or error
```

### Async response codes

| Code | Endpoint | Meaning | Action |
|------|----------|---------|--------|
| 200 | `HEAD` / `GET` | Batch complete, results ready | Read results from response body |
| 204 | `HEAD` | Still processing | Continue polling |
| 202 | `GET /single` | Still processing | Continue polling |
| 400 | `GET /single` | All items failed (client error) | Check error in response body |
| 404 | `HEAD` / `GET` | Batch does not exist | Verify `batch_id` is correct |

> **HEAD vs GET:** Use `HEAD` requests for lightweight status checks (no response body). Use `GET` only when ready to retrieve results to minimize bandwidth.

### When to use asynchronous calls

- Processing takes longer than 30 seconds
- Large batch sizes (100+ items)
- Background processing where immediate results aren't required
- Integration with job queues or workflow systems

## Python Example

A complete Python example showing both synchronous and asynchronous patterns.

```python
import requests
import time

API_TOKEN = "your_api_token"
BASE_URL = "https://agents.botify.com/{organization}/{project}"
AGENT = "ai_visibility_campaigns_list"

headers = {
    "Authorization": f"Bearer {API_TOKEN}",
    "Content-Type": "application/json"
}

single_payload = {
  "item": {}
}


def process_sync(payload: dict) -> dict:
    """Synchronous single-item processing."""
    response = requests.post(
        f"{BASE_URL}/{AGENT}/process",
        headers=headers,
        json=payload
    )
    response.raise_for_status()
    return response.json()


def process_async(
    payload: dict,
    poll_interval: int = 5,
    max_retries: int = 60
) -> dict:
    """Asynchronous single-item processing with polling."""
    # Submit job
    response = requests.post(
        f"{BASE_URL}/{AGENT}/async_process",
        headers=headers,
        json=payload
    )
    batch_id = response.json()["batch_id"]

    # Poll for results using HEAD (lightweight check)
    for _ in range(max_retries):
        status = requests.head(
            f"{BASE_URL}/{AGENT}/async_batches/{batch_id}",
            headers=headers
        )

        if status.status_code == 200:
            result = requests.get(
                f"{BASE_URL}/{AGENT}/async_batches/{batch_id}/single",
                headers=headers
            )
            return result.json()
        elif status.status_code == 204:
            time.sleep(poll_interval)
        else:
            raise Exception(f"Unexpected status: {status.status_code}")

    raise Exception("Max retries exceeded")


def process_async_batch(
    items: list,
    config: dict | None = None,
    poll_interval: int = 5
) -> dict:
    """Asynchronous batch processing with polling."""
    import json as _json

    # Build JSONL payload: first line is config, subsequent lines are items
    lines = [_json.dumps({"config": config or {}, "batch_config": {}})]
    for i, item in enumerate(items):
        lines.append(_json.dumps({"id": f"item_{i}", "item": item}))
    body = "\n".join(lines)

    # Submit batch (JSONL, text/plain)
    response = requests.post(
        f"{BASE_URL}/{AGENT}/async_batch_process",
        headers={**headers, "Content-Type": "text/plain"},
        data=body
    )
    batch_id = response.json()["batch_id"]

    # Poll until ready
    while True:
        status = requests.head(
            f"{BASE_URL}/{AGENT}/async_batches/{batch_id}",
            headers=headers
        )

        if status.status_code == 200:
            results = requests.get(
                f"{BASE_URL}/{AGENT}/async_batches/{batch_id}",
                headers=headers
            )
            return results.json()

        time.sleep(poll_interval)


# Example usage
# result = process_sync(single_payload)
# result = process_async(single_payload)
# results = process_async_batch([{"input": "item1"}, {"input": "item2"}])
```

## Billing

Fixed cost per item requested. This tool reads data Botify already holds for your project and calls no outside service, so nothing is added to the per-call price.

These usage SKUs can be charged on a call.

| SKU | Credits | Description |
| --- | ------- | ----------- |
| Tool call | 1 per request | Charged once per successful item. |


## Schemas

### Item

```json
{
  "type": "object",
  "properties": {
    "include_deleted": {
      "default": false,
      "description": "When true, include campaigns with status deleted. Defaults to false.",
      "title": "Include Deleted",
      "type": "boolean"
    }
  },
  "required": []
}
```

### Config

This agent uses the default config (no custom fields).

### Response

```json
{
  "$defs": {
    "AiVisibilityCampaign": {
      "description": "One AI Visibility campaign, reduced to the fields a caller needs to pick one.",
      "properties": {
        "id": {
          "description": "Campaign id",
          "title": "Id",
          "type": "string"
        },
        "name": {
          "description": "Campaign name",
          "title": "Name",
          "type": "string"
        },
        "campaign_type": {
          "description": "How prompts are sourced: top_gsc_keywords (Search Console), categories (one list of topics per country), or csv_import",
          "enum": [
            "top_gsc_keywords",
            "categories",
            "csv_import"
          ],
          "title": "Campaign Type",
          "type": "string"
        },
        "status": {
          "description": "active, inactive, or deleted",
          "enum": [
            "active",
            "inactive",
            "deleted"
          ],
          "title": "Status",
          "type": "string"
        },
        "providers": {
          "description": "AI platforms the campaign tracks, such as chatgpt, google_gemini, google_ai_overview, google_ai_mode, perplexity",
          "items": {
            "type": "string"
          },
          "title": "Providers",
          "type": "array"
        },
        "size": {
          "description": "Number of prompts the campaign is budgeted to run",
          "title": "Size",
          "type": "integer"
        },
        "countries": {
          "description": "ISO 3166-1 alpha-3 country codes the campaign runs in",
          "items": {
            "type": "string"
          },
          "title": "Countries",
          "type": "array"
        },
        "categories": {
          "description": "Topic names for a categories campaign, in source order. Empty for the other campaign types.",
          "items": {
            "type": "string"
          },
          "title": "Categories",
          "type": "array"
        },
        "intents": {
          "description": "Prompt intents the campaign keeps: informational, commercial, transactional, or all. all and an empty list both mean every intent.",
          "items": {
            "enum": [
              "informational",
              "commercial",
              "transactional",
              "all"
            ],
            "type": "string"
          },
          "title": "Intents",
          "type": "array"
        },
        "contains_brand": {
          "description": "Whether prompts must mention the brand: all_prompts, branded_only, or non_branded_only",
          "enum": [
            "all_prompts",
            "branded_only",
            "non_branded_only"
          ],
          "title": "Contains Brand",
          "type": "string"
        },
        "created_date": {
          "anyOf": [
            {
              "format": "date-time",
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "default": null,
          "description": "When the campaign was created",
          "title": "Created Date"
        },
        "modified_date": {
          "anyOf": [
            {
              "format": "date-time",
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "default": null,
          "description": "When the campaign was last modified",
          "title": "Modified Date"
        }
      },
      "required": [
        "id",
        "name",
        "campaign_type",
        "status",
        "providers",
        "size",
        "countries",
        "categories",
        "intents",
        "contains_brand"
      ],
      "title": "AiVisibilityCampaign",
      "type": "object"
    }
  },
  "properties": {
    "campaigns": {
      "description": "AI Visibility campaigns on the project",
      "items": {
        "$ref": "#/$defs/AiVisibilityCampaign"
      },
      "title": "Campaigns",
      "type": "array"
    },
    "count": {
      "description": "Number of campaigns returned after filtering",
      "title": "Count",
      "type": "integer"
    }
  },
  "required": [
    "campaigns",
    "count"
  ],
  "title": "AiVisibilityCampaignsListProcessedItem",
  "type": "object"
}
```

## Best Practices

**Use exponential backoff for polling.** Start with short intervals (1-2 seconds) and increase the delay between polls to reduce API load.

**Set reasonable timeouts.** For synchronous calls, configure your HTTP client with appropriate timeout values (30-60 seconds).

**Handle rate limits gracefully.** Implement retry logic with backoff when you receive 429 (Too Many Requests) responses.

**Batch when possible.** Use batch endpoints to reduce the number of API calls and improve throughput.