# Portfolio Activation Bridge (`skilled_glee/echoempire-machine-foundry`) Actor

One of 22 EchoEmpire Machine Foundry Actors (catalog: foundry.echoempire.org). This one is a publisher tool: it audits Apify Actor contracts. It is not a scraper. Audits up to 25 Actors for discovery and revenue readiness: activation scores, blockers, capability cards, REST/Python/MCP metadata.

- **URL**: https://apify.com/skilled_glee/echoempire-machine-foundry.md
- **Developed by:** [EchoEmpire Machine Foundry (EchoEmpire LLC)](https://apify.com/skilled_glee) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 1,000 actor auditeds

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

## Apify Actor Discovery & Activation Auditor

Give this Actor up to 25 reviewed Apify Actor contracts and it returns one machine-readable activation report per Actor.

Each report includes contract blockers, an activation score, a Context-compatible capability card, public example-task drafts, a search-intent index, REST/Python/hosted-MCP metadata, and a dataset-schema proposal when one is missing.

### What it does

- Audits input, output, dataset, capability, and use-case contracts.
- Rejects unknown task inputs and public secret fields.
- Generates private task drafts with `isPublic: false`.
- Produces deterministic package and portfolio hashes.
- Isolates invalid Actor entries so one bad contract does not destroy a batch.
- Records `publicationPerformed: false` in every run summary.

### What it does not do

It does not connect to accounts, build Actors, publish tasks, change Store listings, or claim live availability. Generated artifacts require independent live verification and a separate release action.

### Billing

The billing event is `actor-audited`, charged only after a usable activation report has been written. The measured price is `$0.001` per stored report; there is no Actor-start or default-dataset fee.

Published by EchoEmpire Machine Foundry: Apify Actors for AI agents. Catalog: https://foundry.echoempire.org · Publisher: https://apify.com/skilled_glee

# Actor input Schema

## `actors` (type: `array`):

One to 25 reviewed Actor contract objects. Each may include inputSchema, outputContract, datasetSchema, provides, and useCases.

## Actor input object example

```json
{
  "actors": [
    {
      "actorId": "example-actor-id",
      "ownerUsername": "example_owner",
      "slug": "example-actor",
      "name": "Example Actor",
      "description": "Example URLs to structured records.",
      "inputSchema": {
        "type": "object",
        "properties": {
          "urls": {
            "type": "array",
            "items": {
              "type": "string"
            }
          }
        }
      },
      "outputContract": {
        "type": "object",
        "properties": {
          "url": {
            "type": "string"
          },
          "status": {
            "type": "string"
          }
        }
      },
      "datasetSchema": null,
      "provides": [
        "example-extraction"
      ],
      "useCases": []
    }
  ]
}
```

# Actor output Schema

## `reports` (type: `string`):

No description

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

No description

# 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 = {
    "actors": [
        {
            "actorId": "example-actor-id",
            "ownerUsername": "example_owner",
            "slug": "example-actor",
            "name": "Example Actor",
            "description": "Example URLs to structured records.",
            "inputSchema": {
                "type": "object",
                "properties": {
                    "urls": {
                        "type": "array",
                        "items": {
                            "type": "string"
                        }
                    }
                }
            },
            "outputContract": {
                "type": "object",
                "properties": {
                    "url": {
                        "type": "string"
                    },
                    "status": {
                        "type": "string"
                    }
                }
            },
            "datasetSchema": null,
            "provides": [
                "example-extraction"
            ],
            "useCases": []
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("skilled_glee/echoempire-machine-foundry").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 = { "actors": [{
            "actorId": "example-actor-id",
            "ownerUsername": "example_owner",
            "slug": "example-actor",
            "name": "Example Actor",
            "description": "Example URLs to structured records.",
            "inputSchema": {
                "type": "object",
                "properties": { "urls": {
                        "type": "array",
                        "items": { "type": "string" },
                    } },
            },
            "outputContract": {
                "type": "object",
                "properties": {
                    "url": { "type": "string" },
                    "status": { "type": "string" },
                },
            },
            "datasetSchema": None,
            "provides": ["example-extraction"],
            "useCases": [],
        }] }

# Run the Actor and wait for it to finish
run = client.actor("skilled_glee/echoempire-machine-foundry").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 '{
  "actors": [
    {
      "actorId": "example-actor-id",
      "ownerUsername": "example_owner",
      "slug": "example-actor",
      "name": "Example Actor",
      "description": "Example URLs to structured records.",
      "inputSchema": {
        "type": "object",
        "properties": {
          "urls": {
            "type": "array",
            "items": {
              "type": "string"
            }
          }
        }
      },
      "outputContract": {
        "type": "object",
        "properties": {
          "url": {
            "type": "string"
          },
          "status": {
            "type": "string"
          }
        }
      },
      "datasetSchema": null,
      "provides": [
        "example-extraction"
      ],
      "useCases": []
    }
  ]
}' |
apify call skilled_glee/echoempire-machine-foundry --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,skilled_glee/echoempire-machine-foundry"
        }
    }
}
```

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/2TbeQnozDh8XHavTF/builds/mwbNjoOnyXNJ3Ju3T/openapi.json