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Skillyst – AI Resume Analyzer to get more callbacks

Hacker News

Skillyst – AI Resume Analyzer to get more callbacks

Hey everyone! I just launched Skillyst.com — an AI-powered resume analyzer that gives you instant, tailored feedback to help your resume beat the ATS and impress real recruiters. I built Skillyst after seeing so many friends (and myself) struggle with: Sending out tons of resumes and hearing nothing back Not knowing if a resume is even readable by applicant tracking systems Paying for expensive resume consultants with vague advice Why Skillyst is different: It’s like having an AI career coach — but instant and way more affordable Personalized feedback based on your target role & industry ATS compatibility check Tone, grammar & impact analysis No fluff. Just real suggestions you can act on in seconds We’ve had early users tell us they started getting more callbacks within a week of optimizing with Skillyst. “It felt like having a personal career coach who actually knew what recruiters look for.” – one early user If you’re applying for jobs and want to make your resume really stand out before you apply, give it a try: https://skillyst.com I’d love any feedback — good or bad — and I’m happy to answer questions or go deeper into how it works. AMA! — I’m the solo founder and built this to help job seekers cut through the noise. Happy to connect with anyone curious about AI, job hunting tools, or startup life.

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Actual performance

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Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
82%82% 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.
TrustMRRFits verified-revenue profile · Strong signals: personal, users, way · Missing: mobile apps, ios, entrepreneurs
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, new · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
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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