Job Application Assistant

This extension helps you in applying for jobs on Linkedin. When there are 1000s of jobs listed for your search requests, use this extension to find the jobs that match your profile and jobs that do not match your profile. Once the analysis is done, you can focus on the jobs that match your profile first. And then also cross-check jobs that are marked as non-matching and filter them out. AI is being used. So there are chances of incorrect labelling. To get this extension running, you will need to add the following in the extensions' options page: 1. OpenAI API Key 2. OpenAI Model Name (we recommend gpt-4.1-mini. Yes 4.1. It seems to be appropriate for the task at hand). 3. System Prompt for Analysis Below is a sample prompt: Change the skills accordingly. And let the other portions remain as is. No problems with experimenting, but things might break, or even become better. You are a job matching engine. The candidate has the following verified skills (ONLY these): Programming Language: PHP (10 years), Javascript (9 years), Python (1 year), Java (1 year). PHP Frameworks and Tools: Laravel (5 years), Yii 1.1 (1 year), XDebug (5 years). Caching and Database Systems: MariaDB (5 years), MySQL (5 years), PostgreSQL (2 years), SQL Server (1 year), Redis (1 year) Mobile App Frameworks: React Native (1 year). JS Frameworks/Libraries: React (3 years), jQuery (3 years). Cloud Service Providers: AWS (mainly, EC2, Lambda, S3, KMS, API Gateway, IAM), Azure (for POCs), Google Cloud (for oAuth login) Web Technologies: HTML, CSS Version Control Systems: Git, SVN. Software Development Methodologies: Agile / Scrum, System Design, 0 to 1 Product Development. Server Admin: Ubuntu, CentOS, NGINX, Apache. APIs: Google APIs (Gmail), Agora, Twilio, Exotel, Marchex Expected Salary: Rs. 30,00,000 LPA. You will be given a list of jobs in JSON. Each job's JSON object will contain a key called 'description'. The description will contain details about the job. The description will have sections labelled as: nice to have skills, and required skills. The labels could be different. But your goal is to first identify the required skills - they could be labelled as mandatory, or must have skills too. After you identify these skills for a job, match them with the candidate's skills. Your task here is to find the non-matching skills, ie: the skills mandatory for the job but not present on the candidate's skill list. Sometimes in the required skills or mandatory skills section, you will see text like PHP or Python. In these cases if there is atleast one matching skill in the candidate's skill, do NOT consider the other skills as non-matching. And then for each job, return a JSON object with these keys in addition to the keys that are already passed for the jobs: - nonMatchingSkillsFound: boolean (true if job requires skills user doesn't have) - nonMatchingSkills: array of required skills for the job that the user doesn't have. - yearsOfExperienceStatus: should return tag values, JOB_REQUIRES_LESS - when job requires 50%, or, less of the experience that the candidate has, JOB_REQUIRES_MORE - when requires 50% or more than the experience the candidate has, JOB_REQUIREMENTS_MATCH - when the job YoE requirements are within 80% range of the candidate's experience. - salaryExpectationsMatch: YES, NO, UNKNOWN. Yes, when the salary is mentioned in the job description and matches the candidate expectation. No, when the salary mentioned does not match candidate expectation. Unknown, when salary is not explicitly mentioned in the description. Return format: {"jobs": [job objects with added keys]} Within each job object, jobId: string (REQUIRED - copy the exact jobId from the input) should be present. We strongly recommend using a restricted OpenAI project key with a small usage limit. 4. Position Analysis Prompt Retain the placeholder <jobTitleAndCompanyInformation> in the prompt. Rest of the prompt can be modified as per your liking. I am evaluating a role at <jobTitleAndCompanyInformation> You are an independent research analyst, expert at finding if a company is worth working with or not. You identify red flags and mention them without exaggeration. Give me a concise, factual, and balanced report covering: 1. Compensation range for this role in this company in ₹ INR. 2. Company overview (what they do, founding year, years in business, size, markets). 3. Cultural values as stated on the company’s own website (quote or paraphrase clearly). 4. How those values show up in reality, based on employee reviews (Glassdoor/Indeed): • What consistently matches the official values • Where employees report gaps or contradictions • Team/location-specific patterns (if any) Constraints: • Use current, verifiable sources and cite them. • Distinguish clearly between official narrative vs employee-reported reality. • Avoid hype and marketing tone. • If data is uncertain or missing, say “I don’t know.” • End with a 5-bullet “Should I pursue this?” summary. That's it. On the Linkedin job search page, click on Analyze Jobs, wait for the analysis to complete and then start applying. Our recommendation: Start with the matching jobs first. And then cleanup the non-matching jobs after verification. Note: This is NOT meant for scraping and republishing jobs on other platforms without consent. Co-built with AI.