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/linkedin-profile-optimizer

@14d332b
by Serge Bulaevsergebulaev/linkedin-skills3.8k stars
641

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. Not for writing feed content (use linkedin-post-writer).

Use this Skill: https://skilld.dev/gh/sergebulaev/linkedin-skills/linkedin-profile-optimizer

This session only. Nothing lands on disk.

SKILL.md

β‰ˆ109 tokens always: the name and description. β‰ˆ1.3k when used: this file. β‰ˆ3.6k more on demand in 5 files.

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 asks for an audit and pastes their profile text (a bare URL is not readable, see Input)
  • User wants to rewrite their headline, About section, or Featured section
  • User is launching a content strategy and needs the profile to match
  • Any of: "review my profile", "fix my headline", "optimize bio", "profile audit", "LinkedIn optimization"

Input

Paste the profile, do not just link it. The read layer covers posts, comments and engagers; there is no profile actor, so a profile URL cannot be fetched, with an APIFY_TOKEN or without one. Open the profile, copy the sections, paste them in. Screenshots of the visual parts work too.

  • Profile text: headline, About, Experience entries, Skills, custom URL
  • The visual three (photo, banner, Featured): screenshots, or a sentence describing each
  • Goal: clients / job seeking / authority β€” Featured and CTA vary by goal
  • Optional: draft content to grade against the existing profile

If the user supplies only a URL, ask for the text before scoring anything. Never score a section you have not been shown, and never infer profile content from the URL slug.

Output

A structured audit + rewrite in this shape:

  1. Scorecard (9 sections, pass/fail/needs-work)
  2. Priority fixes (ranked by impact)
  3. Before β†’ After rewrites for each failing section
  4. Expected uplift (based on benchmark data)

Steps

  1. Intake. Collect profile state + goal. If only a URL arrived, ask for the pasted text first. Flag missing sections.
  2. Score each of 9 sections against the checklist (see references/).
  3. Rewrite headline using [What You Do] | [Who You Help] [Achieve What Result] β€” fit all 220 chars.
  4. Rebuild About with 7-step structure; verify first 265-275 chars hook before "see more".
  5. Curate Featured (3 strong items) matched to the goal:
    • Clients: lead magnet + case study with results + calendar link
    • Job seeking: portfolio + best work samples + top-performing post
    • Authority: best content + media/podcast features + newsletter signup
  6. Rewrite Experience bullets as action verb + specific metric. Add 5+ skills per role. Pin top 3 skills.
  7. Claim custom URL (linkedin.com/in/firstnamelastname, not the -123abc456 default).
  8. Draft recommendation requests with specifics ("about [project/skill]") β€” don't send LinkedIn's generic template.
  9. Deliver before/after diff + expected uplift (3.9x views, 3-5x conversion, 71% more likely to land interviews).

Nine-component scorecard

# Section Pass criteria (2026)
1 Photo β‰₯400x400, face fills 60% of frame, <3 years old, natural light, slight smile
2 Banner 1584x396, text in right 2/3, high contrast, includes value prop + CTA, tests well on mobile
3 Headline Uses all 220 chars; format `[What You Do]
4 About 200-300 words, first-person, 7-step structure, hook in first 265-275 chars
5 Featured 3 items, matched to goal, custom 1200x627 thumbnails
6 Experience Every bullet = action verb + metric, 5+ skills per role, media attached
7 Skills 50 listed, top 3 pinned, mirrors target job descriptions, β‰₯1 endorsement each
8 Custom URL linkedin.com/in/firstnamelastname (not the default hash)
9 Recommendations At least 3 recent, specific (not generic), from diverse contexts

Key benchmarks (from co.actor research)

  • Optimized About sections: 3.9x more views
  • 5+ listed skills: 3x more connection requests
  • Comprehensive profile: 71% more likely to land interviews
  • Featured section content: 30% longer viewing time
  • Personal founder profile vs company page: 315% more engagement, 270% more conversions

Hard rules

Global voice rules: see root SKILL.md Β§Voice rules. Additional skill-specific rules:

  • First person ("I help...") never third person ("Jane is a passionate...")
  • Never "passionate thought leader" / "driven professional" / "results-oriented" (profile-specific AI vocab)
  • Avoid wall-of-text. Use line breaks in About section
  • 80% of users leave Featured empty. Filling it is a free edge

Reference files

  • references/profile-headline-formulas.md β€” 220-char formula + before/after examples
  • references/about-section-templates.md β€” 7-step structure with character budgets
  • references/featured-section-playbook.md β€” goal-matched content types
  • references/banner-photo-specs.md β€” dimensions, composition, mobile test
  • references/experience-skills-rules.md β€” bullet rewriting + skills strategy + custom URL + recommendations

Related skills

  • linkedin-content-planner β€” post pillars should echo the profile's headline/About thesis
  • linkedin-post-writer β€” Featured section rotates quarterly; pin your flagship post
  • linkedin-humanizer β€” scrub profile copy for the same AI tells we scrub from posts

Source: SKILL.md on GitHub

No alertstoday3 checks Β· Risk SAFE
  • Gen Agent Trust Hubtoday

    The skill is designed to audit and rewrite LinkedIn profiles based on user-provided text and screenshots. The primary security consideration is the ingestion of untrusted profile content, which could potentially contain indirect prompt injections. However, the skill lacks execution capabilities or dangerous tools that would escalate this risk.

  • Sockettoday

    No alerts

  • Snyktoday

    Risk: LOW Β· No issues

Signed by skilld at 14d332b. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 days ago.

Activeupdated 3 days ago

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