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ChameleoCV – Tailored CV and Cover Letter Generator with OpenAI

Hacker News

ChameleoCV – Tailored CV and Cover Letter Generator with OpenAI

What it is: ChameleoCV is an intelligent application designed to revolutionize the job application process. By leveraging the power of the OpenAI API, ChameleoCV streamlines the creation of professional and personalized resumes and cover letters tailored to specific job descriptions. Why I created it: As a software developer with over 5 years of experience, I recently re-entered the job market after taking a break. Over the past few months, I’ve found that securing the roles I want has been challenging. While using ChatGPT to create cover letters for different job descriptions has been helpful, I realized that tailoring both the CV and cover letter for specific job positions significantly increases the chances of landing interviews. However, applying to over 20 positions a week makes tailoring each application manually a time-consuming process. To solve this, I developed ChameleoCV, an application that takes your general CV and a given job description to automatically generate a new, tailored CV and cover letter for each specific role—saving an enormous amount of time. How it works: With your CV provided in JSON format and a job description as input, ChameleoCV creates a tailored prompt for the ChatGPT API. It then calls the API to generate a customized CV and cover letter, which are returned in PDF format for immediate use. GitHub Repository: ChameleoCV on GitHub: https://github.com/mertyertugrul/ChameleoCV I’d greatly appreciate your feedback and constructive code reviews. Let me know how I can improve this project or add features that would make it even more helpful!

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoStrong fit for a featured deal · Strong signals: reviews, calls · Missing: plus, platform, intuitive
54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: code review, ide, io · Missing: https docs, excited, just released
41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: personal, month · Missing: mobile apps, ios, entrepreneurs
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, chatgpt, openai · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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