# Readability Analyzer (`muhammetakkurtt/readability-analyzer`) Actor Instantly analyze readability in text and files (.txt, .pdf, .docx). This advanced tool scores your content with multiple metrics like Flesch-Kincaid, highlights hard-to-read sentences, and provides full text statistics. Perfect for SEO, content marketing and effective communication. - **URL**: https://apify.com/muhammetakkurtt/readability-analyzer.md - **Developed by:** [Muhammet Akkurt](https://apify.com/muhammetakkurtt) (community) - **Categories:** AI, SEO tools, Other - **Stats:** 12 total users, 1 monthly users, 100.0% runs succeeded, 2 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.03 / 1,000 words analyzed for readabilities This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Readability Analyzer The Readability Analyzer is a powerful Apify actor designed to assess the readability of texts. Using various standard scoring formulas, it analyzes provided texts or files and provides a detailed report indicating how easy the content is to read and understand. ### Why Use the Readability Analyzer? This tool offers a fast and reliable solution for improving your content's clarity. It helps you tailor your writing to your target audience and ensures your message is effectively communicated. - **Clarity**: Measures text complexity using multiple established readability formulas. - **Flexibility**: Supports both plain text and various file formats. - **Large Text Support**: Automatically splits texts longer than 10,000 words into chunks for analysis. This ensures that even very large documents can be processed smoothly. - **Easy Integration**: Can be easily run on the Apify platform, and the results can be exported in different formats (JSON, CSV, Excel). ### Features - Analyzes readability by text or file upload. - Supported file formats: `.txt`, `.md`, `.html`, `.pdf`, `.docx`. - Markdown files are rendered before extraction so tables and inline HTML survive conversion to plain text. - Text-based PDFs are supported. Scanned or image-only PDFs are rejected because OCR is not enabled in this actor. - Provides a detailed report with various readability scores (Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning Fog Index, and more). - Automatically splits large texts into parts and analyzes each one. - Includes proxy support and a retry mechanism for more reliable results. - Stores the results in a structured format in the Apify dataset. ### Use Cases - **Content Creation**: For writers, bloggers, and marketers to ensure their content is clear, engaging, and easy to understand for their target audience. - **Education**: For teachers and educators to assess the complexity of educational materials and ensure they are appropriate for the students' reading level. - **Technical Writing**: For technical writers to simplify complex information and make manuals or documentation more user-friendly. - **UX/UI Design**: To ensure that the text used in interfaces is concise and easy for users to comprehend. ### Usage 1. Run this actor in the Apify console. 2. Provide the necessary inputs: - `textContent`: Enter the text you want to analyze for readability (or upload a file below). - `fileUpload`: Upload a file for readability analysis (`.txt`, `.md`, `.html`, `.pdf`, `.docx`). If you upload a file, the text field above is ignored. Scanned or image-only PDFs require OCR and are not processed by this actor. - `proxyConfiguration`: It is recommended to use a proxy for faster and more reliable results. #### Example Input ```json { "textContent": "Barack H. Obama is the 44th President of the United States. His story is the American story — values from the heartland, a middle-class upbringing in a strong family, hard work and education as the means of getting ahead, and the conviction that a life so blessed should be lived in service to others.", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [] } } ```` ### Output The collected data is saved to the Apify dataset. The output data includes the following fields: The `results` object is broken down as follows: #### Readability Scores (`results.readability`) A collection of various readability metrics: - `fleschReadingEase`: Flesch Reading Ease score. - `fleschGradeLevel`: Flesch-Kincaid Grade Level. - `gunningFoxIndex`: Gunning Fog Index. - `smogIndex`: SMOG Index. - `powersSumnerKearl`: Powers-Sumner-Kearl Grade. - `forcastGradeLevel`: FORCAST Grade Level. - `colemanLiauIndex`: Coleman-Liau Index. - `automatedReadabilityIndex`: Automated Readability Index (ARI). - `daleChallReadabilityGrade`: Dale-Chall Readability Grade. - `spacheReadabilityGrade`: Spache Readability Grade. - `linsearWriteGrade`: Linsear Write Grade. #### Sentence-level Analysis (`results.sentences`) An array of objects, where each object provides details about a specific sentence: - `phrase`: The original sentence from the text. - `cleanPhrase`: A cleaned version of the sentence used for analysis. - `isVeryHard`: A boolean indicating if the sentence is considered very difficult to read. - `isHard`: A boolean indicating if the sentence is considered difficult to read. - `wordsOver13Chars`: A list of words in the sentence with more than 13 characters. - `wordsOver4Syllables`: A list of words in the sentence with more than 4 syllables. - `adverbs`: A list of adverbs found in the sentence. #### Text Statistics (`results.textStats`) An object containing overall statistics for the analyzed text: - `letterCount`: Total number of letters. - `sentenceCount`: Total number of sentences. - `uniqueWordCount`: Number of unique words. - `syllableCount`: Total number of syllables. - `averageSyllablesPerWord`: Average syllables per word. - `wordsWithThreeSyllables`: Number of words with three or more syllables. - `percentWordsWithThreeSyllables`: The percentage of words with three or more syllables. - `longestSentence`: The longest sentence in the text. - `paragraphCount`: Total number of paragraphs. - `averageSpeakingTime`: Estimated time to speak the text. - `averageReadingTime`: Estimated time to read the text. - `averageWritingTime`: Estimated time to write the text. ### Example Output ```json { "phrases": [ "Barack H.", "Obama is the 44th President of the United States.", "His story is the American story — values from the heartland, a middle-class upbringing in a strong family, hard work and education as the means of getting ahead, and the conviction that a life so blessed should be lived in service to others." ], "results": { "readability": { "fleschReadingEase": 61.7, "fleschGradeLevel": 9.1, "gunningFoxIndex": 10.9, "smogIndex": 12, "powersSumnerKearl": 2.9, "forcastGradeLevel": 16.4, "colemanLiauIndex": 10.1, "automatedReadabilityIndex": 8.3, "daleChallReadabilityGrade": 4.7, "spacheReadabilityGrade": 4.4, "linsearWriteGrade": 11.4 }, "sentences": [ { "phrase": "Barack H.", "cleanPhrase": "Barack H ", "isVeryHard": false, "isHard": false, "wordsOver13Chars": [], "wordsOver4Syllables": [], "adverbs": [] }, { "phrase": "Obama is the 44th President of the United States.", "cleanPhrase": "Obama is the 44th President of the United States ", "isVeryHard": false, "isHard": false, "wordsOver13Chars": [], "wordsOver4Syllables": [], "adverbs": [] }, { "phrase": "His story is the American story — values from the heartland, a middle-class upbringing in a strong family, hard work and education as the means of getting ahead, and the conviction that a life so blessed should be lived in service to others.", "cleanPhrase": "His story is the American story values from the heartland a middle class upbringing in a strong family hard work and education as the means of getting ahead and the conviction that a life so blessed should be lived in service to others ", "isVeryHard": true, "isHard": false, "wordsOver13Chars": [], "wordsOver4Syllables": [], "adverbs": [ "hard" ] } ], "textStats": { "letterCount": 238, "sentenceCount": 3, "uniqueWordCount": 42, "syllableCount": 80, "totalSyllables": 81, "averageSyllablesPerWord": 1.5, "wordsWithThreeSyllables": 7, "percentWordsWithThreeSyllables": 12.96, "longestSentence": "his story is the American story values from the heartland a middle class upbringing in a strong family hard work and education as the means of getting ahead and the conviction that a life so blessed should be lived in service to others. ", "paragraphCount": 1, "averageSpeakingTime": 0.4, "averageReadingTime": 0.2, "averageWritingTime": 1.4 } } } ``` This example output shows the detailed statistical data resulting from the analysis of the submitted text. The output is a list containing a similar object for each piece of text analyzed. ### Notes - The collected data is stored in Apify's default data store. # Actor input Schema ## `textContent` (type: `string`): Enter the text you want to analyze for readability (or upload a file below). Texts longer than 10,000 words will be automatically processed in chunks. ## `fileUpload` (type: `string`): Upload a file to analyze for readability (.txt, .md, .html, .pdf, .docx). If you upload a file, the text area above will be ignored. Texts longer than 10,000 words will be automatically processed in chunks. Markdown is rendered before extraction, and scanned or image-only PDFs are not supported without OCR. ## `proxyConfiguration` (type: `object`): Using a proxy is recommended for faster and more reliable results ## Actor input object example ```json { "textContent": "Barack H. Obama is the 44th President of the United States. His story is the American story — values from the heartland, a middle-class upbringing in a strong family, hard work and education as the means of getting ahead, and the conviction that a life so blessed should be lived in service to others.", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [] } } ``` # Actor output Schema ## `readabilityAnalysisResults` (type: `string`): Dataset items produced by the actor, including phrases, readability formula scores, per-sentence flags, and aggregate text statistics. # 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("muhammetakkurtt/readability-analyzer").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("muhammetakkurtt/readability-analyzer").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 muhammetakkurtt/readability-analyzer --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=muhammetakkurtt/readability-analyzer", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Readability Analyzer", "description": "Instantly analyze readability in text and files (.txt, .pdf, .docx). This advanced tool scores your content with multiple metrics like Flesch-Kincaid, highlights hard-to-read sentences, and provides full text statistics. Perfect for SEO, content marketing and effective communication.", "version": "0.0", "x-build-id": "jLIWEZLDREg9Vyxqs" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/muhammetakkurtt~readability-analyzer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-muhammetakkurtt-readability-analyzer", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/muhammetakkurtt~readability-analyzer/runs": { "post": { "operationId": "runs-sync-muhammetakkurtt-readability-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/muhammetakkurtt~readability-analyzer/run-sync": { "post": { "operationId": "run-sync-muhammetakkurtt-readability-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "textContent": { "title": "Text to Analyze", "type": "string", "description": "Enter the text you want to analyze for readability (or upload a file below). Texts longer than 10,000 words will be automatically processed in chunks.", "default": "Barack H. Obama is the 44th President of the United States. His story is the American story — values from the heartland, a middle-class upbringing in a strong family, hard work and education as the means of getting ahead, and the conviction that a life so blessed should be lived in service to others." }, "fileUpload": { "title": "Upload a File for Analysis", "type": "string", "description": "Upload a file to analyze for readability (.txt, .md, .html, .pdf, .docx). If you upload a file, the text area above will be ignored. Texts longer than 10,000 words will be automatically processed in chunks. Markdown is rendered before extraction, and scanned or image-only PDFs are not supported without OCR." }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Using a proxy is recommended for faster and more reliable results", "default": { "useApifyProxy": true, "apifyProxyGroups": [] } } } }, "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 } } } } } } } } } } ```