# AI Resume Improver (`moving_beacon-owner1/my-actor-61`) Actor AI Resume Improver ā€” Apify Actor Upload a resume (PDF, DOCX, or paste text) ā†’ get an ATS score (0-100), missing keywords, and actionable improvements tailored to 20+ job roles. - **URL**: https://apify.com/moving\_beacon-owner1/my-actor-61.md - **Developed by:** [Jamshaid Arif](https://apify.com/moving_beacon-owner1) (community) - **Categories:** AI, Jobs, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 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 ## šŸ§  AI Resume Improver ā€” Apify Actor Upload a resume (PDF, DOCX, or paste text) ā†’ get an **ATS score (0-100)**, **missing keywords**, and **actionable improvements** tailored to 20+ job roles. ### šŸš€ Quick Start #### Deploy to Apify ```bash ## 1. Install Apify CLI npm install -g apify-cli ## 2. Login apify login ## 3. Navigate to this folder cd apify-resume-improver ## 4. Push to Apify apify push ```` #### Run Locally ```bash ## Install dependencies pip install -r requirements.txt ## Run with Apify CLI apify run --input='{"resumeUrl": "https://example.com/resume.pdf", "targetRole": "Software Engineer"}' ``` ### šŸ“„ Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `resumeUrl` | string | No\* | Direct URL to a PDF or DOCX file | | `resumeText` | string | No\* | Paste resume text directly | | `targetRole` | enum | Yes | Job role to match keywords against (20 roles available) | | `customKeywords` | string | No | Comma-separated extra keywords from a specific job posting | \* Provide either `resumeUrl` or `resumeText`. #### Supported Roles AI/ML Research Scientist, Backend Developer, Business Analyst, Cloud Architect, Cybersecurity Analyst, Data Analyst, Data Scientist, DevOps Engineer, Financial Analyst, Frontend Developer, Full Stack Developer, HR Manager, Machine Learning Engineer, Marketing Manager, Mobile Developer, Product Manager, Project Manager, Sales Executive, Software Engineer, UX/UI Designer ### šŸ“¤ Output Results are pushed to the **default dataset** and stored in the **key-value store** as `OUTPUT`. ```jsonc { "atsScore": 72, // 0-100 overall score "grade": "B", // A / B / C / D "targetRole": "Software Engineer", "wordCount": 487, "bulletPoints": 12, "quantifiedMetrics": 5, "keywordMatchPercent": 62.5, "scoreBreakdown": { "keywordMatch": { "score": 19, "max": 30 }, "contentRelevance": { "score": 10, "max": 15 }, "resumeSections": { "score": 13, "max": 15 }, "quantifiedImpact": { "score": 13, "max": 15 }, "actionVerbs": { "score": 7, "max": 10 }, "formattingLength": { "score": 7, "max": 10 }, "contactInfo": { "score": 5, "max": 5 } }, "keywords": { "found": ["python", "react", "docker", ...], "missing": ["kubernetes", "system design", ...], "total": 45 }, "actionVerbs": { "strong": ["built", "designed", "implemented", ...], "weak": ["responsible for", "helped"] }, "sectionsDetected": { "summary": true, "experience": true, "education": true, "skills": true, "certifications": false, "projects": true, ... }, "contactInfo": { "email": "john@example.com", "phone": "+1 555-123-4567", "linkedin": "linkedin.com/in/johndoe" }, "improvements": [ { "category": "keywords", "priority": "critical", "message": "Keyword gap is critical (42% match)...", "suggestedKeywords": ["kubernetes", "system design", ...] }, ... ] } ``` ### šŸ“Š Scoring Rubric (100 points) | Category | Weight | What It Measures | |----------|--------|------------------| | Keyword Match | 30 pts | Role-specific keywords found vs missing | | Content Relevance | 15 pts | TF-IDF cosine similarity to ideal profile | | Resume Sections | 15 pts | Essential (summary, experience, education, skills) + bonus sections | | Quantified Impact | 15 pts | Numbers, percentages, dollar amounts in bullets | | Action Verbs | 10 pts | Strong verbs vs weak passive phrases | | Formatting & Length | 10 pts | Word count sweet spot + bullet point usage | | Contact Info | 5 pts | Email, phone, LinkedIn presence | ### šŸ”— API Usage ```bash ## Run via Apify API curl -X POST "https://api.apify.com/v2/acts/YOUR_USERNAME~ai-resume-improver/runs" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer YOUR_API_TOKEN" \ -d '{ "resumeUrl": "https://example.com/resume.pdf", "targetRole": "Data Scientist", "customKeywords": "langchain, RAG, vector database" }' ``` ### šŸ› ļø Tech Stack - **Python 3.11** + Apify SDK - **pdfplumber** ā€” PDF text extraction - **python-docx** ā€” DOCX parsing - **scikit-learn** ā€” TF-IDF vectorization & cosine similarity - **httpx** ā€” Async HTTP for file downloads # Actor input Schema ## `resumeUrl` (type: `string`): Direct URL to a PDF or DOCX resume file. Use this OR resumeText. Supports public links from Google Drive, Dropbox, or any direct file URL. ## `resumeText` (type: `string`): Paste your full resume text here if you don't have a file URL. Include all sections: summary, experience, education, skills, etc. ## `targetRole` (type: `string`): The job role you're applying for ā€” keywords and scoring are matched against this role's requirements. ## `customKeywords` (type: `string`): Comma-separated extra keywords from a specific job description you're targeting. These are checked IN ADDITION to the role's built-in keyword list. ## Actor input object example ```json { "resumeUrl": "https://writing.colostate.edu/guides/documents/resume/functionalSample.pdf", "resumeText": "John Smith\njohn.smith@email.com | linkedin.com/in/johnsmith | (555) 123-4567\n\nSUMMARY\nSoftware Engineer with 5+ years of experience building scalable web applications using Python, React, and AWS. Passionate about clean code, system design, and mentoring junior developers.\n\nEXPERIENCE\nSenior Software Engineer | TechCorp Inc. | 2021 ā€“ Present\nā€¢ Architected microservices platform serving 2M+ daily requests, reducing latency by 40%\nā€¢ Led migration from monolith to Docker/Kubernetes, improving deployment frequency by 300%\nā€¢ Mentored team of 4 junior engineers through code reviews and pair programming\n\nSoftware Engineer | StartupXYZ | 2019 ā€“ 2021\nā€¢ Built REST APIs using Python/Django handling 500K requests/day\nā€¢ Implemented CI/CD pipeline with Jenkins reducing release cycles from 2 weeks to 2 days\nā€¢ Developed React dashboard for real-time analytics used by 50+ enterprise clients\n\nEDUCATION\nB.S. Computer Science | State University | 2019\n\nSKILLS\nPython, JavaScript, TypeScript, React, Django, Node.js, PostgreSQL, MongoDB, Docker, Kubernetes, AWS, Git, CI/CD, REST API, GraphQL, Agile/Scrum\n\nPROJECTS\nā€¢ Open-source CLI tool for API testing (500+ GitHub stars)\nā€¢ Real-time chat application using WebSockets and Redis\n\nCERTIFICATIONS\nā€¢ AWS Solutions Architect Associate\nā€¢ Certified Kubernetes Administrator (CKA)", "targetRole": "Software Engineer", "customKeywords": "fastapi, redis, celery, websockets, postgresql, terraform, github actions, system design, distributed systems" } ``` # 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 = { "resumeUrl": "https://writing.colostate.edu/guides/documents/resume/functionalSample.pdf", "resumeText": `John Smith john.smith@email.com | linkedin.com/in/johnsmith | (555) 123-4567 SUMMARY Software Engineer with 5+ years of experience building scalable web applications using Python, React, and AWS. Passionate about clean code, system design, and mentoring junior developers. EXPERIENCE Senior Software Engineer | TechCorp Inc. | 2021 ā€“ Present ā€¢ Architected microservices platform serving 2M+ daily requests, reducing latency by 40% ā€¢ Led migration from monolith to Docker/Kubernetes, improving deployment frequency by 300% ā€¢ Mentored team of 4 junior engineers through code reviews and pair programming Software Engineer | StartupXYZ | 2019 ā€“ 2021 ā€¢ Built REST APIs using Python/Django handling 500K requests/day ā€¢ Implemented CI/CD pipeline with Jenkins reducing release cycles from 2 weeks to 2 days ā€¢ Developed React dashboard for real-time analytics used by 50+ enterprise clients EDUCATION B.S. Computer Science | State University | 2019 SKILLS Python, JavaScript, TypeScript, React, Django, Node.js, PostgreSQL, MongoDB, Docker, Kubernetes, AWS, Git, CI/CD, REST API, GraphQL, Agile/Scrum PROJECTS ā€¢ Open-source CLI tool for API testing (500+ GitHub stars) ā€¢ Real-time chat application using WebSockets and Redis CERTIFICATIONS ā€¢ AWS Solutions Architect Associate ā€¢ Certified Kubernetes Administrator (CKA)`, "targetRole": "Software Engineer", "customKeywords": "fastapi, redis, celery, websockets, postgresql, terraform, github actions, system design, distributed systems" }; // Run the Actor and wait for it to finish const run = await client.actor("moving_beacon-owner1/my-actor-61").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`šŸ’¾ 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); }); // šŸ“š Want to learn more šŸ“–? Go to ā†’ 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 = { "resumeUrl": "https://writing.colostate.edu/guides/documents/resume/functionalSample.pdf", "resumeText": """John Smith john.smith@email.com | linkedin.com/in/johnsmith | (555) 123-4567 SUMMARY Software Engineer with 5+ years of experience building scalable web applications using Python, React, and AWS. Passionate about clean code, system design, and mentoring junior developers. EXPERIENCE Senior Software Engineer | TechCorp Inc. | 2021 ā€“ Present ā€¢ Architected microservices platform serving 2M+ daily requests, reducing latency by 40% ā€¢ Led migration from monolith to Docker/Kubernetes, improving deployment frequency by 300% ā€¢ Mentored team of 4 junior engineers through code reviews and pair programming Software Engineer | StartupXYZ | 2019 ā€“ 2021 ā€¢ Built REST APIs using Python/Django handling 500K requests/day ā€¢ Implemented CI/CD pipeline with Jenkins reducing release cycles from 2 weeks to 2 days ā€¢ Developed React dashboard for real-time analytics used by 50+ enterprise clients EDUCATION B.S. Computer Science | State University | 2019 SKILLS Python, JavaScript, TypeScript, React, Django, Node.js, PostgreSQL, MongoDB, Docker, Kubernetes, AWS, Git, CI/CD, REST API, GraphQL, Agile/Scrum PROJECTS ā€¢ Open-source CLI tool for API testing (500+ GitHub stars) ā€¢ Real-time chat application using WebSockets and Redis CERTIFICATIONS ā€¢ AWS Solutions Architect Associate ā€¢ Certified Kubernetes Administrator (CKA)""", "targetRole": "Software Engineer", "customKeywords": "fastapi, redis, celery, websockets, postgresql, terraform, github actions, system design, distributed systems", } # Run the Actor and wait for it to finish run = client.actor("moving_beacon-owner1/my-actor-61").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("šŸ’¾ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # šŸ“š Want to learn more šŸ“–? Go to ā†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "resumeUrl": "https://writing.colostate.edu/guides/documents/resume/functionalSample.pdf", "resumeText": "John Smith\\njohn.smith@email.com | linkedin.com/in/johnsmith | (555) 123-4567\\n\\nSUMMARY\\nSoftware Engineer with 5+ years of experience building scalable web applications using Python, React, and AWS. Passionate about clean code, system design, and mentoring junior developers.\\n\\nEXPERIENCE\\nSenior Software Engineer | TechCorp Inc. | 2021 ā€“ Present\\nā€¢ Architected microservices platform serving 2M+ daily requests, reducing latency by 40%\\nā€¢ Led migration from monolith to Docker/Kubernetes, improving deployment frequency by 300%\\nā€¢ Mentored team of 4 junior engineers through code reviews and pair programming\\n\\nSoftware Engineer | StartupXYZ | 2019 ā€“ 2021\\nā€¢ Built REST APIs using Python/Django handling 500K requests/day\\nā€¢ Implemented CI/CD pipeline with Jenkins reducing release cycles from 2 weeks to 2 days\\nā€¢ Developed React dashboard for real-time analytics used by 50+ enterprise clients\\n\\nEDUCATION\\nB.S. Computer Science | State University | 2019\\n\\nSKILLS\\nPython, JavaScript, TypeScript, React, Django, Node.js, PostgreSQL, MongoDB, Docker, Kubernetes, AWS, Git, CI/CD, REST API, GraphQL, Agile/Scrum\\n\\nPROJECTS\\nā€¢ Open-source CLI tool for API testing (500+ GitHub stars)\\nā€¢ Real-time chat application using WebSockets and Redis\\n\\nCERTIFICATIONS\\nā€¢ AWS Solutions Architect Associate\\nā€¢ Certified Kubernetes Administrator (CKA)", "targetRole": "Software Engineer", "customKeywords": "fastapi, redis, celery, websockets, postgresql, terraform, github actions, system design, distributed systems" }' | apify call moving_beacon-owner1/my-actor-61 --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=moving_beacon-owner1/my-actor-61", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Resume Improver", "description": "AI Resume Improver ā€” Apify Actor\nUpload a resume (PDF, DOCX, or paste text) ā†’ get an ATS score (0-100), missing keywords, and actionable improvements tailored to 20+ job roles.", "version": "0.0", "x-build-id": "CXKevFN7ZwmRYyJbQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/moving_beacon-owner1~my-actor-61/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-moving_beacon-owner1-my-actor-61", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/moving_beacon-owner1~my-actor-61/runs": { "post": { "operationId": "runs-sync-moving_beacon-owner1-my-actor-61", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/moving_beacon-owner1~my-actor-61/run-sync": { "post": { "operationId": "run-sync-moving_beacon-owner1-my-actor-61", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "targetRole" ], "properties": { "resumeUrl": { "title": "Resume File URL", "type": "string", "description": "Direct URL to a PDF or DOCX resume file. Use this OR resumeText. Supports public links from Google Drive, Dropbox, or any direct file URL." }, "resumeText": { "title": "Resume Text (paste directly)", "type": "string", "description": "Paste your full resume text here if you don't have a file URL. Include all sections: summary, experience, education, skills, etc." }, "targetRole": { "title": "Target Job Role", "enum": [ "AI/ML Research Scientist", "Backend Developer", "Business Analyst", "Cloud Architect", "Cybersecurity Analyst", "Data Analyst", "Data Scientist", "DevOps Engineer", "Financial Analyst", "Frontend Developer", "Full Stack Developer", "HR Manager", "Machine Learning Engineer", "Marketing Manager", "Mobile Developer", "Product Manager", "Project Manager", "Sales Executive", "Software Engineer", "UX/UI Designer" ], "type": "string", "description": "The job role you're applying for ā€” keywords and scoring are matched against this role's requirements.", "default": "Software Engineer" }, "customKeywords": { "title": "Custom Keywords (optional)", "type": "string", "description": "Comma-separated extra keywords from a specific job description you're targeting. These are checked IN ADDITION to the role's built-in keyword list." } } }, "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 } } } } } } } } } } ```