# Buyer Run Debugging Support (`zentrafoundry/buyer-run-debugging-support`) Actor

Turn buyer-supplied, redacted Apify run symptoms into a bounded intake report with reported failure stage, evidence state, next checks, and a human support handoff. The Actor does not fetch runs, datasets, URLs, or logs.

- **URL**: https://apify.com/zentrafoundry/buyer-run-debugging-support.md
- **Developed by:** [Zentra](https://apify.com/zentrafoundry) (community)
- **Categories:** E-commerce, Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $43.00 / 1,000 apify actor run or buyer defined paid events

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Buyer Run Debugging Support

Buyer Run Debugging Support packages Support retainer + incident report into a buyer-ready Zentra product with source evidence, schemas, sample outputs, QA gates, pricing, forecast

Version: 1.0.0

Pricing model: `PAY_PER_EVENT`.

Default event: `result-delivered`.

The generated actor runs in sample mode by default and only uses live source URLs when the owner has approved source-policy coverage.

Outputs are written to the default Apify dataset using the product schema and public-safe sample evidence generated by Zentra.

This listing is generated from Zentra ProductStudio and excludes secrets, private run IDs, and raw internal validation data.

# Actor input Schema

## `buyerQuery` (type: `string`):

Buyer-safe query or scope for the records returned by this product.

## `taskIntent` (type: `string`):

Stable product-specific purpose for this saved Apify task.

## `sourceMode` (type: `string`):

Sample emits public-safe Agentops Deliverable Status rows. Approved live source mode keeps the same output fields and only uses owner-approved public URLs.

## `outputMode` (type: `string`):

Use sample records for Apify Store QA or buyer-ready records for approved Agentops Deliverable Status delivery.

## `startUrls` (type: `array`):

Public URLs to use for live Agentops Deliverable Status extraction after source-policy approval. Leave empty for sample mode.

## Actor input object example

```json
{
  "buyerQuery": "Deterministic fixture Deliverable Name for Buyer Run Debugging Support",
  "taskIntent": "buyer-ready-product-run",
  "sourceMode": "sample",
  "outputMode": "sample-records",
  "startUrls": []
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "buyerQuery": "Deterministic fixture Deliverable Name for Buyer Run Debugging Support",
    "taskIntent": "buyer-ready-product-run",
    "sourceMode": "sample",
    "outputMode": "sample-records",
    "startUrls": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("zentrafoundry/buyer-run-debugging-support").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "buyerQuery": "Deterministic fixture Deliverable Name for Buyer Run Debugging Support",
    "taskIntent": "buyer-ready-product-run",
    "sourceMode": "sample",
    "outputMode": "sample-records",
    "startUrls": [],
}

# Run the Actor and wait for it to finish
run = client.actor("zentrafoundry/buyer-run-debugging-support").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "buyerQuery": "Deterministic fixture Deliverable Name for Buyer Run Debugging Support",
  "taskIntent": "buyer-ready-product-run",
  "sourceMode": "sample",
  "outputMode": "sample-records",
  "startUrls": []
}' |
apify call zentrafoundry/buyer-run-debugging-support --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,zentrafoundry/buyer-run-debugging-support"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/UzQTlMNUC2p1IEAby/builds/gZtgLPE5owKRchXA8/openapi.json