👥

Linkedin Skills

Claude Code skills for LinkedIn growth: write human-sounding posts, craft comments that get noticed, analyze your feed, and build a publishing cadence — all from your terminal. Plug-and-play skills for content creators, founders, and marketers using Claude Code.

0 installs

Trust: 39 — Low

Social

Ask AI about Linkedin Skills

I know everything about Linkedin Skills. Ask me about installation, configuration, usage, or troubleshooting.

0/500

Loading tools...

Reviews

Documentation

LinkedIn Marketing Skills for Claude

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.

Install

Pick whichever way you use Claude:

claude.ai (web)

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

Claude Desktop (Mac / Windows)

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

OpenClaw

Open your OpenClaw working directory

Clone the skills into it:

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

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.

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

Claude Code (CLI / VS Code / JetBrains)

/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

What you can do

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.

The 10 skills

Skill	What it does
Post Writer	Drafts viral-ready posts using 10 proven 2026 hook formulas (anaphora, R.I.P. obituary, year-over-year pivot, curiosity gap, and 6 more)
Comment Drafter	Drafts a comment on any LinkedIn post from its URL
Reply Handler	Drafts a reply to any comment, correctly handling LinkedIn's 2-level thread flattening
Post Audit	Checks your draft against 2026 algorithm rules and AI-detection patterns before you publish
Humanizer	Strips em dashes, AI vocabulary ("leverage", "delve", "harness"), rule-of-three lists, and other AI fingerprints. Bundles three sub-tools: AI-emoji density scorer, multi-detector spread tester (GPTZero, Originality.ai, ZeroGPT, Sapling, Copyleaks), and a rule-explainer reference for defending stylistic choices.
Hook Extractor	Reverse-engineers the hook formula from any viral post. Returns a blank template you can fill with your own topic
Content Planner	Creates a 7-day plan with daily post topics, formats, hooks, posting times, and comment targets
Engagement Monitor	Two read-side workflows: (1) tracks your comment threads for author replies and drafts follow-ups in the 6-24h window; (2) pulls likers and commenters on any post and groups them by ICP fit (peer / aspirational / prospect).
Profile Optimizer	Rewrites your headline, About section, Featured section, and Experience for 2026 conversion patterns
Employee Advocacy	Plans a team LinkedIn program: 14-day launch, posting cadence, brand governance, ROI tracking

Optional: read LinkedIn data with Apify

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:

Use case	Actor	Cost
Post body by URL	`supreme_coder/linkedin-post`	$1 / 1,000
Comments + replies on a post	`apimaestro/linkedin-post-comments-replies-engagements-scraper-no-cookies`	$5 / 1,000
Your own recent comments	`apimaestro/linkedin-profile-comments`	$5 / 1,000
Likers + commenters on any post	`scraping_solutions/linkedin-posts-engagers-likers-and-commenters-no-cookies`	$5 / 1,000

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.

Optional: auto-post with Publora

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.

What is Publora?

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.

Setup (2 minutes)

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.

Voice rules

Every skill follows these rules automatically:

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

Troubleshooting

Problem	Fix
Skills don't activate when I ask about LinkedIn	Make sure you installed via the Skills panel or `/plugin install`. Try starting a new conversation.
"Publora API key not provided"	Your `.env` file is missing or in the wrong folder. It should be in the `linkedin-skills/` root.
"401 Unauthorized" from Publora	Your API key expired. Go to Publora Settings > API > Create a new key.
"404 on comment/post"	Your `LINKEDIN_PLATFORM_ID` is wrong. Go to Publora Channels and copy the full `linkedin-...` string.
"400 reactionType" error	Known Publora quirk. The skills handle this automatically. If you're calling the API manually, use PRAISE (not CELEBRATE), INTEREST (not INSIGHTFUL).
`pip install` fails	Use a virtual environment: `python -m venv venv && source venv/bin/activate && pip install requests python-dotenv`

Cross-cutting references

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

For developers: runtime compatibility, URL parsing, and internals

Runtime compatibility

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

Runtime	Auto-discovers skills?	Setup
Claude Code (CLI, Desktop, Web, IDE)	Yes	Install via plugin or clone. Skills activate on matching prompts.
Anthropic Managed Agents (`/v1/agents`)	Yes	Pass skill files in the agent context.
OpenClaw	Manual	Mount the repo, add system prompt pointing to `skills/*/SKILL.md`.
Cursor / Codex / Cline / Aider	No	Read `SKILL.md` files as prompt context; import `lib/` as Python.
Manus	No	Upload `references/` as knowledge base. Call Publora API directly.
LangChain / AutoGen	No	Use `lib/` as a package; feed `references/` as prompt context.

OpenClaw quickstart

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."

Generic Python agent quickstart

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")

URL handling

LinkedIn has three post URN types. The lib/url_parser.py handles all of them:

URL fragment	URN
`/posts/slug-activity-7448...`	`urn:li:activity:7448...`
`/posts/slug-share-7449...`	`urn:li:share:7449...`
`/feed/update/urn:li:ugcPost:7447...`	`urn:li:ugcPost:7447...`

Comment URLs include a commentUrn query param. The parser extracts both post_urn and comment_id.

Thread flattening

LinkedIn flattens reply threads to 2 levels. When replying to a reply, parentComment must point to the top-level comment URN, not the reply's URN. The linkedin-reply-handler skill handles this correctly.

Testing the parser

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

References

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

License

MIT. Powered by Publora.

Anthropic Skills repo
awesome-claude-skills directory