Linkedin Reader Agent Skill

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 globally
npm install -g @jackwener/opencli

If SETUP_NEEDED, guide the user through setup:

Setup

opencli requires Node.js >= 21 and a Chrome browser with the Browser Bridge extension:

• 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
• Login to linkedin.com in Chrome — opencli reuses your existing browser session
• Verify connectivity:

opencli doctor

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

Common setup issues

| Symptom | Fix |

|---------|-----|

| Extension not connected | Install Browser Bridge extension in Chrome and ensure it's enabled |

| Daemon not running | Run opencli doctor — it auto-starts the daemon |

| No session for linkedin.com | Login to linkedin.com in Chrome, then retry |

| AuthRequiredError | LinkedIn session expired — refresh linkedin.com in Chrome and log in again |

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.

| User Request | Command | Key Flags |

|---|---|---|

| Setup check | opencli doctor | — |

| Home feed / posts | opencli linkedin timeline | --limit N (default 20, max 100) |

| Search for jobs | opencli linkedin search "QUERY" | --location, --limit N (default 10, max 100), --details |

| Finance job search | opencli linkedin search "QUERY" | --experience-level, --job-type, --remote, --company, --date-posted, --start |

Step 3: Execute the Command

General pattern

# Read LinkedIn feed posts
opencli linkedin timeline --limit 20 -f json

# Search for finance/trading jobs
opencli linkedin search "quantitative analyst" --limit 10 -f json
opencli linkedin search "portfolio manager" --location "New York" --limit 15 -f json

# Detailed job listings with descriptions
opencli linkedin search "financial analyst" --details --limit 10 -f json

Key rules

• Check setup first — run opencli doctor before any other command if unsure about connectivity
• Use -f json or -f yaml for structured output when processing data programmatically
• Use -f csv when the user wants spreadsheet-compatible output
• Use --limit N to control result count — start with 10-20 unless the user asks for more
• For job search, use filters — --location, --experience-level, --job-type, --remote, --date-posted to narrow results
• NEVER execute write operations — this skill is read-only; do not post, like, comment, connect, message, or apply to jobs

Output format flag (-f)

| Format | Flag | Best for |

|---|---|---|

| Table | -f table (default) | Human-readable terminal output |

| JSON | -f json | Programmatic processing, LLM context |

| YAML | -f yaml | Structured output, readable |

| Markdown | -f md | Documentation, reports |

| CSV | -f csv | Spreadsheet export |

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

After fetching data, present it clearly for financial research:

• Summarize key content — highlight the most relevant posts or jobs for the user's research
• Include attribution — show author name, headline, post text, and engagement (reactions, comments)
• Provide URLs when the user might want to read the full post or job listing
• For feed posts, highlight market commentary, analyst takes, earnings reactions, and professional sentiment
• For job search results, present title, company, location, salary (when available), and posting date
• Flag sentiment — note bullish/bearish professional sentiment, consensus vs contrarian views
• Treat sessions as private — never expose browser session details

Step 5: Diagnostics

If something isn't working, run:

opencli doctor

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

Error Reference

| Error | Cause | Fix |

|-------|-------|-----|

| Extension not connected | Browser Bridge not installed/enabled | Install extension and enable it in Chrome |

| No session | Not logged into linkedin.com | Login to linkedin.com in Chrome |

| AuthRequiredError | LinkedIn login wall detected | Refresh linkedin.com and log in again |

| EmptyResultError | No results found for query | Broaden search terms or check feed has content |

| Rate limited | Too many requests | Wait a few minutes, then retry |

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.