Pricing

Pay per event

Lead Scoring & AI Qualification — Scores, Reasons & Openers

Score leads 1–10 against your ICP, add a concise reason and personalized cold opener, and filter to qualified rows when needed. Turn any lead list into a prioritized outreach list. Requires your own OpenAI-compatible API key; model usage is billed by your provider.

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Pay per event

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Rook DataTools

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20 days ago

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Lead generation

You can access the Lead Scoring & AI Qualification — Scores, Reasons & Openers programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

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          "leads": {
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            "type": "array",
            "description": "Leads to qualify — an array of objects (any shape: name, website, phone, category, etc.) or plain strings. Leave empty if you're using an Input dataset instead."
          },
          "inputDatasetId": {
            "title": "Input dataset ID (optional)",
            "type": "string",
            "description": "Qualify the output of another Actor run: paste its dataset ID (e.g. a directory scraper or the Website Contact Extractor). Combined with any inline leads. Requires 'apifyToken' below."
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          "apifyToken": {
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          },
          "icpDescription": {
            "title": "Ideal Customer Profile (ICP)",
            "type": "string",
            "description": "Describe your perfect customer in plain words. Be opinionated — specifics produce sharper scoring. e.g. 'Independent restaurants and bars in US metros, not chains, that likely lack a modern POS.'"
          },
          "offerDescription": {
            "title": "Your offer",
            "type": "string",
            "description": "What you sell, in one or two sentences. Used to write the personalized opener."
          },
          "scoreThreshold": {
            "title": "Qualified threshold",
            "minimum": 1,
            "maximum": 10,
            "type": "integer",
            "description": "Leads scoring at or above this (1-10) are marked qualified.",
            "default": 7
          },
          "onlyReturnQualified": {
            "title": "Only return qualified leads",
            "type": "boolean",
            "description": "If on, only leads meeting the threshold are written to the output dataset.",
            "default": false
          },
          "model": {
            "title": "Model",
            "type": "string",
            "description": "Chat-completions model name on your provider. Leave blank to use the built-in default."
          },
          "apiBaseUrl": {
            "title": "API base URL",
            "type": "string",
            "description": "Base URL for your model provider's chat-completions API. Leave blank to use the built-in default."
          },
          "apiKey": {
            "title": "API key (your own)",
            "type": "string",
            "description": "Your API key for your chosen model provider. Stored as a secret; used only to call the model on your behalf. This is why you pay only pennies per lead here — the model cost is billed to your own account."
          },
          "maxLeads": {
            "title": "Max leads per run",
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            "type": "integer",
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            "default": 1000
          },
          "concurrency": {
            "title": "Concurrency",
            "minimum": 1,
            "maximum": 10,
            "type": "integer",
            "description": "How many leads to score in parallel (1-10).",
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          }
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                "example": "READY"
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                  "userAgent": {
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Lead Scoring & AI Qualification — Scores, Reasons & Openers OpenAPI definition

OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.

OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.

By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.

You can download the OpenAPI definitions for Lead Scoring & AI Qualification — Scores, Reasons & Openers from the options below:

OpenAPI.json

If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.

You can also check out our other API clients:

Lead Scoring & AI Qualification — Scores, Reasons & Openers API in Python

Lead Scoring & AI Qualification — Scores, Reasons & Openers API in JavaScript

Lead Scoring & AI Qualification — Scores, Reasons & Openers API through CLI

Lead Scoring & AI Qualification — Scores, Reasons & Openers API

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