# Agent Decision Tools — five decision-ready, x402-grade APIs (`draeg82/agent-decision-tools`) Actor

Decision API for AI agents: UK carbon-aware scheduling (NESO), FX quote audit (Frankfurter), domain expiry/DNSSEC (RDAP), npm/PyPI package health, UK business-day deadlines (GOV.UK). Zero keys, authoritative free upstreams, decision-ready output.

- **URL**: https://apify.com/draeg82/agent-decision-tools.md
- **Developed by:** [Andy Mitchell](https://apify.com/draeg82) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 decision tool completeds

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

## agent-decision-tools

Deterministic decision APIs for AI agents and automation: UK carbon-aware scheduling
(NESO), FX quote audit (Frankfurter/central-bank), domain expiry + DNSSEC audit (RDAP),
package health (npm/PyPI), and UK business-day deadlines (GOV.UK).

Built on the demand-validated decision-tools service: this actor exposes the same five
decision-grade tools over the Apify cloud with **per-run charge events** (PAY\_PER\_EVENT),
so external buyers get a single billed, documented API.

### Tools

| tool | what it returns | data source |
|------|-----------------|-------------|
| carbon | carbon-aware scheduling window for a given duration + location | NESO (UK) + global fallback |
| fx | audited FX quote (base rate + explicit markup + provenance) | Frankfurter (central-bank) |
| domain | expiry, registrar, nameserver, DNSSEC, security posture | RDAP (IANA/Nominet/Verisign/PDN) |
| package | package "health" score: downloads, deps, version, last publish, source | npm / PyPI |
| calendar | next N UK business dates / business-day arithmetic (skip weekends + GOV.UK bank holidays) | GOV.UK (England & Wales) |

### Calling

Single tool: `{ "tool": "carbon", "args": { "durationMinutes": 240 } }`
Batch: `{ "batch": [ {"tool":"domain","args":{"domain":"example.com"}}, ... ] }`

### Pricing

PAY\_PER\_EVENT: `apify-actor-start` $0.005 + `decision-tool-completed` $0.01 per run,
20% Apify margin. Free to try; billed per completed run.

### Outputs

`OUTPUT` — JSON report `{status, version, count_requested, count_ok, count_failed,
error?, results[]}` where each result is `{tool, args, status, output, error?, ms}`.
Default dataset mirrors the same per-result rows. All data sourced from public, named,
authoritative endpoints with per-field `source` provenance.

# Actor input Schema

## `tool` (type: `string`):

The decision tool to call. If omitted, a non-empty "batch" is required.

## `args` (type: `object`):

Tool-specific arguments. carbon: {durationMinutes: 30-720, from?, to?}; fx: {sourceCurrency, targetCurrency, sourceAmount, quotedTargetAmount, fee?}; domain: {domain}; package: {ecosystem: npm|pypi, packageName}; calendar: {startDate: YYYY-MM-DD, businessDays, division?}

## `batch` (type: `array`):

Optional list of {tool, args}. When provided (and non-empty), all are run and results combined. Takes precedence over a single tool.

## Actor input object example

```json
{
  "tool": "calendar",
  "args": {},
  "batch": []
}
```

# Actor output Schema

## `dataset` (type: `string`):

Per-run dataset of decision tool results: status, count\_requested, count\_ok, count\_failed, error, results\[] (one row per requested tool call: tool, args, status, output, error, ms).

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("draeg82/agent-decision-tools").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("draeg82/agent-decision-tools").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 '{}' |
apify call draeg82/agent-decision-tools --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,draeg82/agent-decision-tools"
        }
    }
}
```

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/xxHLf9FuVh0KndKqA/builds/nf14jfLuYN5soO0ni/openapi.json