10 skills that help Claude write LinkedIn posts, comments, and replies in your voice. They draft content, strip AI tells, and wait for your approval before anything gets published. No coding required.

Pick whichever way you use Claude:

1. Open https://claude.ai/code
2. Go to Skills in the sidebar
3. Click Add from GitHub
4. Paste: sergebulaev/linkedin-skills
5. Done. The skills activate automatically when you ask about LinkedIn.

1. Open Claude Desktop
2. Open Settings (gear icon)
3. Go to Skills
4. Click Add from GitHub
5. Paste: sergebulaev/linkedin-skills
6. Done. Start a new conversation and ask Claude to write a LinkedIn post.

1. Open your OpenClaw working directory
2. Clone the skills into it:

   git clone https://github.com/sergebulaev/linkedin-skills.git

3. In OpenClaw settings, add this to your system prompt:

   You have LinkedIn marketing skills in ./linkedin-skills/.
   For any LinkedIn task, read the relevant skills/*/SKILL.md first.
   Use lib/url_parser.py for URL parsing,
       lib/apify_client.py for reading posts / comments / engagers,
       lib/publora_client.py for publishing actions.
   

4. Done. Ask OpenClaw to write a LinkedIn post or comment.

/plugin marketplace add sergebulaev/linkedin-skills
/plugin install linkedin-skills@linkedin-skills

Or clone the repo and open it as your working directory:

git clone https://github.com/sergebulaev/linkedin-skills.git
cd linkedin-skills

Once installed, just talk to Claude. The right skill activates automatically.

Write a post:

"Write me a LinkedIn post about why AI agencies are replacing traditional ones. Make it viral."

Comment on someone's post:

"Comment on this post: https://linkedin.com/posts/... — I want to add a thoughtful take."

Check a draft before publishing:

"Audit this post draft for AI tells and algorithm issues: [paste your text]"

Reverse-engineer a viral post:

"What hook formula does this post use? https://linkedin.com/posts/..."

Plan your week:

"Create a 7-day LinkedIn content plan. I'm a B2B SaaS founder targeting VPs of Marketing."

Rewrite your profile:

"Optimize my LinkedIn profile for inbound leads: https://linkedin.com/in/yourname"

Remove AI tells from any text:

"Humanize this text: [paste AI-generated draft]"

Every skill shows you a draft first and waits for your OK before doing anything. Nothing gets posted without your approval.

Four of the skills (Comment Drafter, Reply Handler, Hook Extractor, Engagement Monitor) can read post bodies, comment threads, your own recent comments, and the people who liked or commented on any post. Without an Apify token they fall back to asking you to paste the relevant text. With one, they fetch automatically.

Apify free tier ships with $5/month of credit, which goes a long way at $1-$5 per 1,000 results. The skills use four no-cookies actors:

Setup: drop APIFY_TOKEN=apify_api_... into your .env. The thin client at lib/apify_client.py exposes fetch_post, fetch_post_comments, fetch_user_recent_comments, and fetch_post_engagers.

A typical creator running daily comment ops + a weekly engager-analytics sweep stays under $2/month, well inside the free tier.

By default, skills draft content for you to copy-paste into LinkedIn. If you want Claude to publish directly to your LinkedIn (and optionally to X, Threads, Instagram), connect Publora. It takes about 2 minutes.

Publora is a publishing API that handles LinkedIn's quirks (3 different URL formats, reaction type mismatches, thread flattening bugs). The free tier gives you 15 posts/month.

Step 1. Sign up at https://app.publora.com/signup (free)

Step 2. Connect LinkedIn: click Channels in the left sidebar, then Add Channel, pick LinkedIn, authorize.

Step 3. Find your Platform ID: go to Channels, click your LinkedIn account. The ID looks like linkedin-ABC123DEF. Copy the whole thing including linkedin-.

Step 4. Get your API key: click Settings (gear icon, bottom-left), then API, then Create Key. Copy the sk_... string.

Step 5. Create a file called .env in the linkedin-skills folder:

PUBLORA_API_KEY=sk_paste_your_key_here
LINKEDIN_PLATFORM_ID=linkedin-paste_your_id_here

If you cloned the repo, you can copy the template instead:

cp .env.example .env

Then open .env and replace the placeholders with your real values.

Step 6. Install two small Python packages:

pip install requests python-dotenv

Step 7. Test it. Ask Claude:

"Schedule a test LinkedIn post via Publora 2 hours from now: 'testing the API connection'. Show me the response, then delete it."

If Publora returns a scheduled-post ID, you're set. If you get HTTP 401, your API key is wrong. If you get HTTP 400 about a missing platformId, your LINKEDIN_PLATFORM_ID isn't set. See Troubleshooting.

Every skill follows these rules automatically:

1. No em dashes. Biggest AI tell in 2026.
2. Capitalize names. Always. Lowercase reads as disrespectful.
3. No AI vocabulary: "leverage", "fundamentally", "streamline", "harness", "delve", "unlock", "foster".
4. Specific numbers beat adjectives. "$14,200" beats "significant savings".
5. One sharp insight per comment beats three vague ones.
6. 200-350 chars for comments, 900-1,300 chars for posts.

• references/industry-benchmarks.md — engagement rates, time-per-post, reach multipliers across industries
• references/engagement-metrics-taxonomy.md — what to measure at post / account / team / business level

linkedin-skills/
├── skills/          ← SKILL.md frontmatter; native to Claude Code, others read as markdown
├── lib/             ← pure Python, works in any agent runtime
├── references/      ← pure markdown, works anywhere
└── scripts/         ← pure Python CLI, works anywhere

git clone git@github.com:sergebulaev/linkedin-skills.git

# Add to OpenClaw system prompt:
# "You have LinkedIn marketing skills in ./linkedin-skills/.
#  Read the relevant skills/*/SKILL.md before any LinkedIn task.
#  Use lib/url_parser.py for URL parsing,
#      lib/apify_client.py for reading posts / comments / engagers,
#      lib/publora_client.py for publishing."

import sys; sys.path.insert(0, "path/to/linkedin-skills")
from lib import parse_linkedin_url, PubloraClient, ApifyClient

parsed = parse_linkedin_url("https://www.linkedin.com/posts/slug-activity-7448808898326654978-iW20")
print(parsed["post_urn"])  # urn:li:activity:7448808898326654978

# Read side (Apify)
apify = ApifyClient()  # reads APIFY_TOKEN from env
post = apify.fetch_post(post_url="https://www.linkedin.com/posts/...")
engagers = apify.fetch_post_engagers(post_url="https://www.linkedin.com/posts/...", max_items=50)

# Write side (Publora)
client = PubloraClient()  # reads PUBLORA_API_KEY from env
client.create_comment(post_urn=parsed["post_urn"], message="draft", platform_id="linkedin-xxx")

python lib/url_parser.py "https://www.linkedin.com/posts/dharmesh_activity-7448808898326654978-iW20"

• Publora API docs — endpoint reference for the publishing layer
• Apify console — manage actors, tokens, and usage for the read layer
• 360Brew paper — LinkedIn's ranking foundation model
• AuthoredUp 2026 reach data — format-level reach benchmarks

MIT. Powered by Publora.

• Anthropic Skills repo
• awesome-claude-skills directory