Linkedin Reader

LinkedIn Skill (Read-Only)

Reads LinkedIn for financial research using opencli, a universal CLI tool that bridges web services to the terminal via browser session reuse.

This skill is read-only. It is designed for financial research: reading professional commentary on markets, monitoring analyst posts, searching finance/trading jobs, and tracking professional sentiment. It does NOT support posting, liking, commenting, connecting, messaging, or any write operations.

Important: opencli reuses your existing Chrome login session — no API keys or cookie extraction needed. Just be logged into linkedin.com in Chrome and have the Browser Bridge extension installed.

Step 1: Ensure opencli Is Installed and Ready

Current environment status:

!`(command -v opencli && opencli doctor 2>&1 | head -5 && echo "READY" || echo "SETUP_NEEDED") 2>/dev/null || echo "NOT_INSTALLED"`

If the status above shows READY, skip to Step 2. If NOT_INSTALLED, install first:

# Install opencli globallynpm install -g @jackwener/opencli

If SETUP_NEEDED, guide the user through setup:

Setup

opencli requires Node.js >= 20 and a Chrome browser with the Browser Bridge extension:

1. Install the Browser Bridge extension:
   • Download the latest opencli-extension-v{version}.zip from the GitHub Releases page
   • Unzip it, open chrome://extensions in Chrome, and enable Developer mode
   • Click Load unpacked and select the unzipped folder
2. Login to linkedin.com in Chrome — opencli reuses your existing browser session
3. Verify connectivity:

opencli doctor

This auto-starts the daemon, verifies the extension is connected, and checks session health.

Common setup issues

Step 2: Identify What the User Needs

Match the user's request to one of the read commands below, then use the corresponding command from references/commands.md.

Step 3: Execute the Command

General pattern

# Read LinkedIn feed postsopencli linkedin timeline --limit 20 -f json
# Search for finance/trading jobsopencli linkedin search "quantitative analyst" --limit 10 -f jsonopencli linkedin search "portfolio manager" --location "New York" --limit 15 -f json
# Detailed job listings with descriptionsopencli linkedin search "financial analyst" --details --limit 10 -f json

Key rules

1. Check setup first — run opencli doctor before any other command if unsure about connectivity
2. Use -f json or -f yaml for structured output when processing data programmatically
3. Use -f csv when the user wants spreadsheet-compatible output
4. Use --limit N to control result count — start with 10-20 unless the user asks for more
5. For job search, use filters — --location, --experience-level, --job-type, --remote, --date-posted to narrow results
6. Read-only — don't post, like, comment, connect, message, or apply to jobs

Output format flag (-f)

Output columns

Timeline posts include: rank, author, author_url, headline, text, posted_at, reactions, comments, url.

Job search results include: rank, title, company, location, listed, salary, url. With --details: also description, apply_url.

Step 4: Present the Results

Lead with what matters for the user's research question rather than a raw dump. For feed posts, attribute each one (author, headline, text, reactions and comments, URL), highlight market commentary, analyst takes, and earnings reactions, and note the bullish or bearish lean and where views are consensus or contrarian. For job results, give title, company, location, salary when available, posting date, and the listing URL. Keep browser session details private.

Step 5: Diagnostics

If something isn't working, run:

opencli doctor

This checks daemon status, extension connectivity, and browser session health.

Error Reference

Reference Files

• references/commands.md — Complete read command reference with all flags, research workflows, and usage examples

Read the reference file when you need exact command syntax, research workflow patterns, or output details.