/linkedin-profile-optimizer

name: linkedin-profile-optimizer
description: "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)."

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** — 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 → 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]` — 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]") — 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** | ≥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] | [Who You Help] [Result]` | | 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, ≥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` §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` — 220-char formula + before/after examples
• `references/about-section-templates.md` — 7-step structure with character budgets
• `references/featured-section-playbook.md` — goal-matched content types
• `references/banner-photo-specs.md` — dimensions, composition, mobile test
• `references/experience-skills-rules.md` — bullet rewriting + skills strategy + custom URL + recommendations

Related skills

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