# Public Structured Data & Rich Results Readiness Agent (`jacksu/public-structured-data-readiness-agent`) Actor Audit public JSON-LD, Microdata, RDFa, Schema.org types, rich-result candidate signals, missing recommended fields, and change hashes with useful-result pricing. - **URL**: https://apify.com/jacksu/public-structured-data-readiness-agent.md - **Developed by:** [jack su](https://apify.com/jacksu) (community) - **Categories:** SEO tools, AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 useful structured-data readiness 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/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## Public Structured Data & Rich Results Readiness Agent Turn public web pages into compact structured-data readiness records for SEO audits, AI agents, RAG preparation, content QA, and rich-result hygiene checks. The Actor fetches the supplied public page URLs and audits JSON-LD, Microdata, and RDFa signals. It returns Schema.org types, detected formats, fields, missing recommended fields, rich-result candidate types, diagnostics, a readiness score, confidence score, and a stable structured-data hash for change tracking. Rich-result candidate signals are not a guarantee that Google or another search engine will display a rich result. Search engines apply their own eligibility, quality, policy, and rendering rules. This Actor reports public page evidence and readiness diagnostics. ### How To Use It For a first-pass inventory, provide public page URLs and leave Schema focus types empty: ```json { "pageUrls": ["https://blog.apify.com/web-scraping-guide/"], "schemaFocusTypes": [], "previousStructuredDataRecords": [], "requestTimeoutSecs": 20 } ```` For targeted checks, add `schemaFocusTypes` such as `Article`, `Product`, `FAQPage`, `BreadcrumbList`, `Organization`, `WebSite`, or `SoftwareApplication`. If focus types are supplied, useful-result charging requires at least one matching Schema.org type in the public page evidence. For repeat monitoring, pass previous dataset records from this Actor in `previousStructuredDataRecords`. If the structured-data hash is unchanged, the record is written as `changeStatus: "unchanged"` without the useful event charge. ### What It Finds Useful evidence can include: - JSON-LD, Microdata, and RDFa formats detected on the page - Schema.org types and structured-data item counts - fields found on each structured-data item - missing recommended fields for common rich-result candidate types - rich-result candidate categories such as Article, Product, FAQPage, HowTo, BreadcrumbList, Recipe, Review, VideoObject, and SoftwareApplication - matched focus types, readiness score, confidence score, diagnostics, evidence URLs, and a stable structured-data hash ### Pricing Pay-per-event pricing is designed to stay predictable: - `apify-actor-start`: a tiny run-start fee - `useful-structured-data-readiness-result`: charged only for useful page-level structured-data readiness records - no `apify-default-dataset-item` If `schemaFocusTypes` are supplied, useful-result charging requires at least one matching Schema.org type. Invalid inputs, duplicate equivalent URLs, private-network targets, query/fragment/token inputs, failed fetches, focus misses, unchanged records, and blank/weak pages do not charge the useful event. Pages with no structured data can still be useful paid readiness audit results when the public HTML was fetched and clear diagnostics are returned. ### Output Each page returns one record with fields such as: - `status`, `changeStatus`, `inputUrl`, `finalUrl`, and `siteOriginUrl` - `pageTitle`, `pageDescription`, `schemaTypes`, and `formatsDetected` - `structuredDataItems`, `structuredDataItemCount`, and `richResultCandidates` - `matchedSchemaFocusTypes`, `structuredDataHash`, `readinessScore`, `confidenceScore`, `missingFields`, and `diagnostics` ### Boundaries This Actor is a page-level structured-data readiness audit, not Google's Rich Results Test, a SERP scraper, rank tracker, website crawler, screenshot tool, article extractor, product extractor, API-docs scanner, contact finder, or legal/trust evidence tool. It fetches only the provided public page URLs. It does not log in, use cookies, render JavaScript, run a full-site crawl, bypass paywalls, scrape search-engine results, or enrich private persons. ### Not For This Actor is not an official rich-results validator, rank tracker, sitemap crawler, Lighthouse runner, JavaScript renderer, search-engine scraper, or SEO recommendation engine. It extracts bounded public structured-data evidence for downstream review. # Actor input Schema ## `pageUrls` (type: `array`): Public HTTP/HTTPS page URLs to audit. First run creates page-level structured-data readiness records; later runs can compare against previousStructuredDataRecords. Query parameters, fragments, credentials, path params, and private-network addresses are rejected. ## `schemaFocusTypes` (type: `array`): Optional Schema.org types to look for, such as Article, Organization, Product, FAQPage, BreadcrumbList, WebSite, or SoftwareApplication. Leave empty for a first-pass inventory. When supplied, useful-result charging requires at least one matching type. ## `previousStructuredDataRecords` (type: `array`): Previous dataset records from this Actor for repeat monitoring. Leave empty for a first-pass audit. If the structured-data hash is unchanged, the result is diagnostic and does not charge the useful event. ## `requestTimeoutSecs` (type: `integer`): Maximum time in seconds to wait for each public page request. ## Actor input object example ```json { "pageUrls": [ "https://blog.apify.com/web-scraping-guide/" ], "schemaFocusTypes": [], "previousStructuredDataRecords": [], "requestTimeoutSecs": 20 } ``` # Actor output Schema ## `datasetId` (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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("jacksu/public-structured-data-readiness-agent").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("jacksu/public-structured-data-readiness-agent").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).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 jacksu/public-structured-data-readiness-agent --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jacksu/public-structured-data-readiness-agent", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Public Structured Data & Rich Results Readiness Agent", "description": "Audit public JSON-LD, Microdata, RDFa, Schema.org types, rich-result candidate signals, missing recommended fields, and change hashes with useful-result pricing.", "version": "0.1", "x-build-id": "vrbhmPAYSmlB15BUo" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jacksu~public-structured-data-readiness-agent/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jacksu-public-structured-data-readiness-agent", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jacksu~public-structured-data-readiness-agent/runs": { "post": { "operationId": "runs-sync-jacksu-public-structured-data-readiness-agent", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jacksu~public-structured-data-readiness-agent/run-sync": { "post": { "operationId": "run-sync-jacksu-public-structured-data-readiness-agent", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "pageUrls" ], "properties": { "pageUrls": { "title": "Page URLs", "minItems": 1, "maxItems": 20, "type": "array", "description": "Public HTTP/HTTPS page URLs to audit. First run creates page-level structured-data readiness records; later runs can compare against previousStructuredDataRecords. Query parameters, fragments, credentials, path params, and private-network addresses are rejected.", "items": { "type": "string" }, "default": [ "https://blog.apify.com/web-scraping-guide/" ] }, "schemaFocusTypes": { "title": "Schema focus types", "maxItems": 20, "type": "array", "description": "Optional Schema.org types to look for, such as Article, Organization, Product, FAQPage, BreadcrumbList, WebSite, or SoftwareApplication. Leave empty for a first-pass inventory. When supplied, useful-result charging requires at least one matching type.", "items": { "type": "string" }, "default": [] }, "previousStructuredDataRecords": { "title": "Previous structured-data records", "type": "array", "description": "Previous dataset records from this Actor for repeat monitoring. Leave empty for a first-pass audit. If the structured-data hash is unchanged, the result is diagnostic and does not charge the useful event.", "items": { "type": "object" }, "default": [] }, "requestTimeoutSecs": { "title": "Request timeout", "minimum": 5, "maximum": 60, "type": "integer", "description": "Maximum time in seconds to wait for each public page request.", "default": 20 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```