After seeing "LinkedIn gurus" charge hundreds of dollars for basic profile reviews, I built a free tool to automate this analysis.
Just paste your LinkedIn profile URL and get instant insights:
Section-by-section analysis and score with description of reason of the score
Specific recommendations with explanations
Visual score breakdown
Tried your tool - takes some time to process, but the result is surprisingly actionable. What you base your analysis on? Did you consult LinkedIn experts for your algorithm?
Great idea! It’s refreshing to see someone offering a free tool to counter the overhyped “guru” industry on LinkedIn. I tried it out, and the interface is clean and easy to use—props for making it frictionless with no signup required.
The section-by-section breakdown is insightful, and I like how the recommendations are actionable rather than generic fluff. One suggestion: it might be useful to incorporate examples or templates for high-scoring profiles to help users better visualize the recommendations.
Quick question: how are you prioritizing the recommendations? Are they weighted based on the potential impact, or is it more of a generalized scoring system?
Looking forward to seeing how this evolves—keep up the great work!
5 comments
[ 3.4 ms ] story [ 19.3 ms ] threadAfter seeing "LinkedIn gurus" charge hundreds of dollars for basic profile reviews, I built a free tool to automate this analysis. Just paste your LinkedIn profile URL and get instant insights:
Section-by-section analysis and score with description of reason of the score Specific recommendations with explanations Visual score breakdown
Try it without signup: https://app.2pr.io/linkedin_profile_review Would love your feedback on the analysis logic and which recommendations you find most useful.
I'll be here to answer questions. This is our first Show HN.
I believe the app version are on par in terms of quality/depth but is much more detailed
The section-by-section breakdown is insightful, and I like how the recommendations are actionable rather than generic fluff. One suggestion: it might be useful to incorporate examples or templates for high-scoring profiles to help users better visualize the recommendations.
Quick question: how are you prioritizing the recommendations? Are they weighted based on the potential impact, or is it more of a generalized scoring system?
Looking forward to seeing how this evolves—keep up the great work!