# ARIA Landmark Auditor (`phoenix2810/aria-landmark-auditor`) Actor Audit one public page for semantic HTML and ARIA landmark structure. Checks main, navigation, banner, contentinfo, repeated unlabeled landmarks, score, and accessibility recommendations. - **URL**: https://apify.com/phoenix2810/aria-landmark-auditor.md - **Developed by:** [Sanskar Jaiswal](https://apify.com/phoenix2810) (community) - **Categories:** SEO tools, Developer tools, Open source - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## ARIA Landmark Auditor Fetches one public page and audits its semantic HTML and ARIA landmark structure. It checks for a single main landmark, repeated landmarks that need accessible labels, and duplicate banner or contentinfo landmarks. ### Use cases - Accessibility QA for page templates, product pages, landing pages, and checkout flows. - SEO and technical QA during site launches or migrations. - Scheduled monitoring for CMS templates where landmark regressions can affect many pages. - Developer-tool pipelines that need one structured JSON result per page. ### Input | Field | Type | Required | Description | | --- | --- | --- | --- | | `startUrl` | string | yes | Public HTTP or HTTPS page URL to audit. Credentials and private network targets are rejected. | | `timeoutSeconds` | integer | no | Page request timeout from 3 to 30 seconds. Default is 10. | | `maxLandmarks` | integer | no | Maximum landmark detail objects to include in output. Default is 100. | ### Output The actor pushes one dataset item per run. | Field | Type | Description | | --- | --- | --- | | `inputUrl` | string | Original URL from input. | | `normalizedInputUrl` | string | Input URL after adding a default HTTPS scheme if omitted. | | `finalUrl` | string | Final fetched URL after safe redirects. | | `status` | integer or null | HTTP status code, or null when the fetch failed. | | `ok` | boolean | True when the page fetched successfully and scored at least 90. | | `checkedAt` | string | ISO timestamp for the audit. | | `landmarkCount` | integer | Total semantic or ARIA landmarks found. | | `mainCount` | integer | Count of `main` or `role="main"` landmarks. | | `navigationCount` | integer | Count of `nav` or `role="navigation"` landmarks. | | `bannerCount` | integer | Count of `header` or `role="banner"` landmarks. | | `contentinfoCount` | integer | Count of `footer` or `role="contentinfo"` landmarks. | | `complementaryCount` | integer | Count of `aside` or `role="complementary"` landmarks. | | `searchCount` | integer | Count of `role="search"` landmarks. | | `formLandmarkCount` | integer | Count of `role="form"` landmarks. | | `regionCount` | integer | Count of `role="region"` landmarks. | | `unlabeledRepeatedCount` | integer | Repeated navigation, complementary, form, region, or search landmarks without `aria-label` or `aria-labelledby`. | | `landmarks` | array | Sampled landmark objects with tag, role, explicit role, label, id, and class name. | | `unlabeledRepeatedLandmarks` | array | Sampled repeated landmarks that need labels. | | `score` | integer | Accessibility readiness score from 0 to 100. | | `grade` | string | Letter grade from A to F. | | `issues` | array | Human-readable problems found. | | `recommendations` | array | Actionable fixes. | | `error` | string or null | Fetch or validation error, if any. | ### Example input ```json { "startUrl": "https://example.com", "timeoutSeconds": 10, "maxLandmarks": 100 } ```` ### Example output ```json { "inputUrl": "https://example.com", "normalizedInputUrl": "https://example.com/", "finalUrl": "https://example.com/", "status": 200, "ok": false, "checkedAt": "2026-07-17T00:00:00.000Z", "landmarkCount": 4, "mainCount": 1, "navigationCount": 2, "bannerCount": 1, "contentinfoCount": 0, "complementaryCount": 0, "searchCount": 0, "formLandmarkCount": 0, "regionCount": 0, "unlabeledRepeatedCount": 1, "landmarks": [ { "tag": "nav", "role": "navigation", "explicitRole": null, "label": "Primary", "id": null, "className": null } ], "unlabeledRepeatedLandmarks": [ { "tag": "nav", "role": "navigation", "explicitRole": null, "label": null, "id": null, "className": null } ], "score": 90, "grade": "A", "issues": ["1 repeated landmark(s) lack accessible labels"], "recommendations": ["Add aria-label or aria-labelledby to repeated navigation, search, form, complementary, or region landmarks."], "error": null } ``` ### Security This actor only fetches public HTTP and HTTPS URLs. It rejects URL credentials, localhost and private IP literals, hostnames that resolve to private IP ranges, and redirects to private targets. Response bodies are capped at 2 MB. ### Pricing | Event | Suggested price | Notes | | --- | ---: | --- | | Actor start | `$0.005` | Charged once per run. | | Page audited | `$0.01` | Charged per dataset item pushed. | ### FAQ #### Does this run a browser? No. It fetches HTML and parses landmark elements and roles. This keeps runs fast and inexpensive. #### Does it validate every WCAG rule? No. It focuses on landmark structure. Use it alongside broader accessibility scanners when you need full WCAG coverage. #### Can it audit private staging sites? No. Private network targets are blocked for SSRF safety. Use public staging URLs only. #### What should a good page have? Most pages should have one main landmark and clear labels for repeated navigation, search, form, complementary, or region landmarks. # Actor input Schema ## `startUrl` (type: `string`): Public HTTP or HTTPS page URL to audit. Credentials and private network targets are rejected. ## `timeoutSeconds` (type: `integer`): Request timeout for the page fetch. ## `maxLandmarks` (type: `integer`): Maximum landmark details to include in the dataset item. ## Actor input object example ```json { "startUrl": "https://example.com", "timeoutSeconds": 10, "maxLandmarks": 100 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrl": "https://example.com" }; // Run the Actor and wait for it to finish const run = await client.actor("phoenix2810/aria-landmark-auditor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrl": "https://example.com" } # Run the Actor and wait for it to finish run = client.actor("phoenix2810/aria-landmark-auditor").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 '{ "startUrl": "https://example.com" }' | apify call phoenix2810/aria-landmark-auditor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=phoenix2810/aria-landmark-auditor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ARIA Landmark Auditor", "description": "Audit one public page for semantic HTML and ARIA landmark structure. Checks main, navigation, banner, contentinfo, repeated unlabeled landmarks, score, and accessibility recommendations.", "version": "0.1", "x-build-id": "On3K06uDNltdwOdKS" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/phoenix2810~aria-landmark-auditor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-phoenix2810-aria-landmark-auditor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/phoenix2810~aria-landmark-auditor/runs": { "post": { "operationId": "runs-sync-phoenix2810-aria-landmark-auditor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/phoenix2810~aria-landmark-auditor/run-sync": { "post": { "operationId": "run-sync-phoenix2810-aria-landmark-auditor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrl" ], "properties": { "startUrl": { "title": "Page URL", "type": "string", "description": "Public HTTP or HTTPS page URL to audit. Credentials and private network targets are rejected." }, "timeoutSeconds": { "title": "Timeout seconds", "minimum": 3, "maximum": 30, "type": "integer", "description": "Request timeout for the page fetch.", "default": 10 }, "maxLandmarks": { "title": "Max landmarks in output", "minimum": 1, "maximum": 300, "type": "integer", "description": "Maximum landmark details to include in the dataset item.", "default": 100 } } }, "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 } } } } } } } } } } ```