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Skill

linkedin-profile-score

by henriquesantanati

AI Summary

Analyze a LinkedIn profile from its native CSV data export and produce a comprehensive score with actionable recommendations to improve recruiter visibility and hiring chances. This skill requires the user's LinkedIn data exported as CSV files (the default format LinkedIn provides). 1. Go to LinkedI

Install

Copy this and paste it into Claude Code, Cursor, or any AI assistant:

I want to install the "linkedin-profile-score" skill in my project.

Please run this command in my terminal:
# Install skill into your project
mkdir -p .claude/skills/linkedin-profile-score && curl --retry 3 --retry-delay 2 --retry-all-errors -o .claude/skills/linkedin-profile-score/SKILL.md "https://raw.githubusercontent.com/henriquesantanati/linkedin-profile-score/main/SKILL.md"

Then restart Claude Code (or reload the window in Cursor) so the skill is picked up.

Description

Audit and score a LinkedIn profile from its native CSV data export. Analyzes profile sections for recruiter visibility, keyword optimization, and credibility. Use when the user provides a folder of CSV files from a LinkedIn data export and wants to optimize their profile for job searching. Triggers on: audit my LinkedIn, review my profile, LinkedIn optimization, profile score, score my profile, LinkedIn audit, optimize my LinkedIn, LinkedIn CSV. Do NOT use for writing LinkedIn posts, managing connections, job application tracking, or general career coaching.

Prerequisites

This skill requires the user's LinkedIn data exported as CSV files (the default format LinkedIn provides). How to get the data: • Go to LinkedIn → Settings → Data Privacy → Get a copy of your data • Select "Download larger data archive" and request the archive • Wait for the email (usually 24-72h) • Download and unzip the ZIP file • Provide the path to the unzipped folder Expected CSV files (read all that exist in the export folder): | File | Content | |------|---------| | Profile.csv | Name, headline, location, summary, industry | | Positions.csv | Work history (title, company, description, dates) | | Skills.csv | Listed skills | | Connections.csv | Network connections | | Shares.csv or Posts.csv | Posts and activity | | Company Follows.csv | Companies and organizations followed | | Member_Follows.csv | People followed | | Languages.csv | Profile language proficiency | | Certifications.csv | Licenses and certifications | | Education.csv | Educational background | | Email Addresses.csv | Contact email(s) | Note: LinkedIn occasionally changes file names between export versions. If a file is not found by exact name, look for partial matches (e.g., a file containing "position" or "experience" in its name). Adapt to whatever CSV files are present.

LinkedIn Profile Score

Analyze a LinkedIn profile from its native CSV data export and produce a comprehensive score with actionable recommendations to improve recruiter visibility and hiring chances.

Step 1: Locate Input

Ask the user for the path to their unzipped LinkedIn data export folder. List the CSV files found and confirm which ones are available before proceeding. Privacy note: Inform the user that their export contains personal data (name, email, work history, connections). This data is processed locally by the LLM and is not stored or shared, but the user should be aware of what they are providing.

Step 2: Read Profile Data

Read all available CSV files. Parse them as standard CSV (comma-delimited, with headers in the first row). Track which files are present and which are missing. Missing files mean those sections receive no score (not zero, just excluded from the weighted calculation and weights redistributed proportionally).

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Health Signals

MaintenanceCommitted 1mo ago
Active
AdoptionUnder 100 stars
33 ★ · Niche
DocsREADME + description
Well-documented

GitHub Signals

Stars33
Forks1
Issues0
Updated1mo ago
View on GitHub
MIT License

My Fox Den

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Works With

Claude Code