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Skills/himself65/finance-skills/linkedin-reader
linkedin-reader logo

linkedin-reader

himself65/finance-skills
699 installs3K stars
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Installation

npx skills add https://github.com/himself65/finance-skills --skill linkedin-reader

Summary

>

SKILL.md

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:

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

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

Common setup issues

SymptomFix
Extension not connectedInstall Browser Bridge extension in Chrome and ensure it's enabled
Daemon not runningRun opencli doctor — it auto-starts the daemon
No session for linkedin.comLogin to linkedin.com in Chrome, then retry
AuthRequiredErrorLinkedIn 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 RequestCommandKey Flags
Setup checkopencli doctor—
Home feed / postsopencli linkedin timeline--limit N (default 20, max 100)
Search for jobsopencli linkedin search "QUERY"--location, --limit N (default 10, max 100), --details
Finance job searchopencli 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

  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. NEVER execute write operations — this skill is read-only; do not post, like, comment, connect, message, or apply to jobs

Output format flag (-f)

FormatFlagBest for
Table-f table (default)Human-readable terminal output
JSON-f jsonProgrammatic processing, LLM context
YAML-f yamlStructured output, readable
Markdown-f mdDocumentation, reports
CSV-f csvSpreadsheet 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:

  1. Summarize key content — highlight the most relevant posts or jobs for the user's research
  2. Include attribution — show author name, headline, post text, and engagement (reactions, comments)
  3. Provide URLs when the user might want to read the full post or job listing
  4. For feed posts, highlight market commentary, analyst takes, earnings reactions, and professional sentiment
  5. For job search results, present title, company, location, salary (when available), and posting date
  6. Flag sentiment — note bullish/bearish professional sentiment, consensus vs contrarian views
  7. 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

ErrorCauseFix
Extension not connectedBrowser Bridge not installed/enabledInstall extension and enable it in Chrome
No sessionNot logged into linkedin.comLogin to linkedin.com in Chrome
AuthRequiredErrorLinkedIn login wall detectedRefresh linkedin.com and log in again
EmptyResultErrorNo results found for queryBroaden search terms or check feed has content
Rate limitedToo many requestsWait 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.

Score

0–100
57/ 100

Grade

C

Popularity17/30

699 installs — growing adoption. Source repo has 2,806 GitHub stars.

Completeness19/30

Documented: full SKILL.md body, one-line install. Missing: description, category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Linkedin Reader skill score badge previewScore badge

Markdown

[![Linkedin Reader skill](https://www.remoteopenclaw.com/skills/himself65/finance-skills/linkedin-reader/badges/score.svg)](https://www.remoteopenclaw.com/skills/himself65/finance-skills/linkedin-reader)

HTML

<a href="https://www.remoteopenclaw.com/skills/himself65/finance-skills/linkedin-reader"><img src="https://www.remoteopenclaw.com/skills/himself65/finance-skills/linkedin-reader/badges/score.svg" alt="Linkedin Reader skill"/></a>

Linkedin Reader FAQ

How do I install the Linkedin Reader skill?

Run “npx skills add https://github.com/himself65/finance-skills --skill linkedin-reader” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Linkedin Reader skill do?

> The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Linkedin Reader skill free?

Yes. Linkedin Reader is a free, open-source skill published from himself65/finance-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Linkedin Reader work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Linkedin Reader works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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