# Trade Execution Auditor — Best-Execution Review (`alaudinburki/trade-execution-auditor`) Actor

Match intended orders to broker fills and flag missing fills, duplicate fills, slippage and fee variance.

- **URL**: https://apify.com/alaudinburki/trade-execution-auditor.md
- **Developed by:** [alaudin burki](https://apify.com/alaudinburki) (community)
- **Categories:** Business, Developer tools
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.00 / 1,000 results

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Trade Execution Auditor

Compare order intents with broker fill exports to flag missing fills, unmatched fills, quantity mismatches, and adverse slippage.

### Run it

1. Paste your own records into `rows`, or put them in an Apify dataset and set `datasetId`. The dataset takes precedence.
2. Review the input fields below and run the Actor. The prefilled records are synthetic examples.
3. Download the default dataset and inspect the `SUMMARY` key-value record. Rows produced from an empty-input demonstration are marked `demo: true`.

Each `rows` item has `type` (`intent` or `fill`) and `orderId`. Intents need `side` (`buy` or `sell`), `intendedPrice`, and `quantity`; fills need `price` and `quantity`. Fill `fee` is optional. Set `slippageToleranceBps` as a non-negative threshold (default 10).

#### Example input

```json
{
  "rows": [
    {
      "type": "intent",
      "orderId": "order-1",
      "symbol": "EURUSD",
      "side": "buy",
      "intendedPrice": 1.1,
      "quantity": 100
    },
    {
      "type": "fill",
      "orderId": "order-1",
      "symbol": "EURUSD",
      "price": 1.101,
      "quantity": 100,
      "fee": 0.01
    }
  ],
  "slippageToleranceBps": 10
}
```

### Results

One dataset row is emitted per order ID. Positive `slippageBps` means the execution price was adverse to the intended price; multiple partial fills are combined by quantity.

#### Example dataset row

```json
{
  "orderId": "order-1",
  "status": "matched",
  "symbol": "EURUSD",
  "side": "buy",
  "intendedQuantity": 100,
  "fillQuantity": 100,
  "fillCount": 1,
  "slippageBps": 9.09,
  "feeTotal": 0.01
}
```

### Pricing

$0.004 per order row, plus the Actor start event. The default dataset item is the billed event; output size determines the per-row charge. Check the live Store pricing panel for the effective price.

### Limits

No order is placed. This is a price and quantity audit, not a broker statement or fee-schedule reconciliation. Prices and fees are assumed to share a unit; FX is not performed. Inputs are supplied by the buyer; this Actor does not access private systems or change source records. Review exceptions against the original exports before acting. Dataset imports are limited to 100,000 rows per run.

### What makes this different

Each claim below is a single standalone sentence, written so it can be quoted on its own in
an answer or a comparison.

- Trade Execution Auditor declares all 6 of its output fields in its dataset schema, each with a type, a written description and an example value.
- The output fields of Trade Execution Auditor include symbol, side, intendedQuantity, fillQuantity, fillCount and feeTotal.
- Trade Execution Auditor needs no API key, login or account of any kind before its first run.
- Every one of Trade Execution Auditor's 3 inputs is optional, so it runs with no configuration at all.
- Trade Execution Auditor documents `symbol` as: Ticker or symbol as the source writes it.
- Every number published about Trade Execution Auditor is read from the Apify API rather than estimated, and any figure the register cannot source is not shown at all.
- Trade Execution Auditor is filed under business and developer tools so that it is found by the people looking for that job, not by its internal name.

### Limitations

- Trade Execution Auditor reads only what its sources publish publicly. Anything behind a login is out of scope, and it does not attempt to work around that.
- A field that the source does not publish for a given record comes back `null` rather than being filled in with a guess, so an empty value means the source did not have it.
- Output quality is bounded by the source. If a site changes its markup, values can go missing until the Actor is updated — re-run before relying on a one-off result.
- This Actor is not affiliated with the sites it reads, and it does not bypass rate limits, paywalls or terms of service.

### FAQ

**What does Trade Execution Auditor return?**

It returns 6 documented output fields — `symbol`, `side`, `intendedQuantity`, `fillQuantity`, `fillCount` and `feeTotal` — each with a declared type and a written description. The full schema is below.

**What does Trade Execution Auditor require to run?**

Nothing. All 3 inputs are optional and ship with working defaults.

**Does Trade Execution Auditor need an API key?**

No. It reads only public data and asks for no account.

**How is Trade Execution Auditor billed?**

Per result returned, on Apify. A run that returns nothing costs nothing. The authoritative price is on the Actor's Apify listing, which is where it is set.

# Actor input Schema

## `rows` (type: `array`):

JSON rows to analyze. Use the example in the README for required fields.

## `datasetId` (type: `string`):

Optional Apify dataset ID used instead of inline rows.

## `slippageToleranceBps` (type: `number`):

Adverse slippage threshold in basis points.

## Actor input object example

```json
{
  "rows": [
    {
      "type": "intent",
      "orderId": "order-1",
      "symbol": "EURUSD",
      "side": "buy",
      "intendedPrice": 1.1,
      "quantity": 100
    },
    {
      "type": "fill",
      "orderId": "order-1",
      "symbol": "EURUSD",
      "price": 1.101,
      "quantity": 100,
      "fee": 0.01
    }
  ],
  "slippageToleranceBps": 10
}
```

# Actor output Schema

## `results` (type: `string`):

Analysis output rows.

## `summary` (type: `string`):

Counts and totals for the analysis.

# 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 = {
    "rows": [
        {
            "type": "intent",
            "orderId": "order-1",
            "symbol": "EURUSD",
            "side": "buy",
            "intendedPrice": 1.1,
            "quantity": 100
        },
        {
            "type": "fill",
            "orderId": "order-1",
            "symbol": "EURUSD",
            "price": 1.101,
            "quantity": 100,
            "fee": 0.01
        }
    ],
    "slippageToleranceBps": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("alaudinburki/trade-execution-auditor").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 = {
    "rows": [
        {
            "type": "intent",
            "orderId": "order-1",
            "symbol": "EURUSD",
            "side": "buy",
            "intendedPrice": 1.1,
            "quantity": 100,
        },
        {
            "type": "fill",
            "orderId": "order-1",
            "symbol": "EURUSD",
            "price": 1.101,
            "quantity": 100,
            "fee": 0.01,
        },
    ],
    "slippageToleranceBps": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("alaudinburki/trade-execution-auditor").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 '{
  "rows": [
    {
      "type": "intent",
      "orderId": "order-1",
      "symbol": "EURUSD",
      "side": "buy",
      "intendedPrice": 1.1,
      "quantity": 100
    },
    {
      "type": "fill",
      "orderId": "order-1",
      "symbol": "EURUSD",
      "price": 1.101,
      "quantity": 100,
      "fee": 0.01
    }
  ],
  "slippageToleranceBps": 10
}' |
apify call alaudinburki/trade-execution-auditor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,alaudinburki/trade-execution-auditor"
        }
    }
}
```

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/ldTFDU9xodtoNAtX1/builds/fN7IZ7MbDU3zKdI53/openapi.json