linkedin-profile-optimizer
Audit and rewrite a LinkedIn profile end-to-end for 2026: headline, About 7-step, Featured, banner, photo, Experience metrics, Skills, custom URL, recommendations. Triggers on "review my profile", "rewrite my headline", "fix my About", "optimize banner", "profile audit", "LinkedIn bio". Converts resume-style profiles to ones that convert 3-5x better.
npx skills add sergebulaev/linkedin-skills --skill linkedin-profile-optimizer --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LinkedIn Profile Optimizer Audit the nine components of a LinkedIn profile (photo, banner, headline, About, Featured, Experience, Skills, custom URL, recommendations) against 2026 best practices, then rewrite each section that needs it. Optimized profiles get ~3.9x more views and convert visitors 3-5x better than default/resume-style profiles. ## When to use - User pastes their LinkedIn profile
What does the linkedin-profile-optimizer skill do?
Audit and rewrite a LinkedIn profile end-to-end for 2026: headline, About 7-step, Featured, banner, photo, Experience metrics, Skills, custom URL, recommendations. Triggers on "review my profile", "rewrite my headline", "fix my About", "optimize banner", "profile audit", "LinkedIn bio". Converts resume-style profiles to ones that convert 3-5x better.
How do I install it?
Run `npx skills add sergebulaev/linkedin-skills --skill linkedin-profile-optimizer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From sergebulaev/linkedin-skills, a repository with 357 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.