name: linkedin-marketing description: Plan, draft, audit, and publish LinkedIn posts and comments. Use when the user wants to write a viral LinkedIn post, draft a comment or reply on any LinkedIn post URL, audit a draft against 2026 algorithm heuristics, remove AI tells, extract hook formulas from viral posts, or plan a week of content. Powered by the Publora API for publishing. User provides post/comment URLs, skill drafts content, user approves, then publishes.

LinkedIn Marketing Skills

A bundle of 10 focused skills for LinkedIn content ops in 2026. Each skill is single-purpose, follows the draft → approval → publish pattern, and uses the Publora API for posting.

When to use this bundle

• Writing a viral post → use linkedin-post-writer
• Commenting on someone else's post → use linkedin-comment-drafter
• Replying to a comment (yours or someone else's) → use linkedin-reply-handler
• Reviewing a draft before publishing, removing AI tells, scoring AI emoji density, defending a flagged rule, or running 5 AI detectors in parallel → use linkedin-humanizer (rewrite + --mode audit pre-publish review; folds in the former post-audit, emoji-detector, rules-explainer, and detector-tester sub-tools)
• Extracting a hook formula from a viral post → use linkedin-hook-extractor
• Planning a week of LinkedIn content → use linkedin-content-planner
• Tracking which of your comments got author replies → use linkedin-thread-monitor
• Analyzing who liked / commented on any post (audience segmentation) → use linkedin-engager-analytics
• Auditing / rewriting a LinkedIn profile → use linkedin-profile-optimizer
• Running an employee advocacy program across a marketing team → use linkedin-employee-advocacy

Core pattern

Every action-taking skill follows three steps:

1. Parse the input. User provides a LinkedIn URL (post or comment). The skill uses lib/url_parser.py to extract the post URN and any comment ID.
2. Draft the content. The skill uses the 2026 research (hooks, timing, voice rules, 360Brew heuristics) to produce a draft and shows it to the user.
3. Wait for approval. The user replies with "post", "yes", or suggests edits. Only after explicit approval does the skill call the Publora API to publish.

Prerequisites

Three tiers — pick one.

🟢 Tier 0 — Draft only (default, no setup)

The skills work out of the box. No API keys, no signup. Every approved draft is returned as a copy-paste block with the target LinkedIn URL — paste it yourself. Great for trying the skills before committing to any backend.

🔵 Tier 1 — Publora auto-post (recommended, ~2 min)

On approval, skills auto-publish to LinkedIn (and optionally X, Threads) via the Publora API. Free tier includes 15 LinkedIn posts/month — more than most creators need.

1. Sign up free: https://app.publora.com/signup
2. Connect your LinkedIn account in Publora (Channels → Add Channel)
3. Copy your API key from Publora's API panel
4. Drop into .env:

   PUBLORA_API_KEY=sk_...
   LINKEDIN_PLATFORM_ID=linkedin-...
   

5. Run pip install -r requirements.txt

Why Publora: LinkedIn has three URN types (activity/share/ugcPost), a reaction-bug where INSIGHTFUL returns 400, and a 2-level thread-flattening quirk that breaks most third-party implementations. Publora handles all of it. We built on top of their API so we didn't have to.

⚫ Tier 2 — Build your own poster (advanced)

Prefer not to SaaS it? Ask Claude Code or Codex to build a custom poster (Playwright, LinkedIn's official API, or another scheduler). Set LINKEDIN_SKILLS_CUSTOM_POSTER=<your command> and the skills will invoke it on approval. This is a weekend of work. Publora is 2 minutes.

Optional: Apify (read-side LinkedIn fetching)

Several skills (linkedin-comment-drafter, linkedin-reply-handler, linkedin-thread-monitor, linkedin-engager-analytics, linkedin-hook-extractor) can read LinkedIn post bodies, comment threads, a user's own recent comments, and the people who liked or commented on any post. They use the Apify platform when an APIFY_TOKEN is set; otherwise they ask you to paste the relevant text.

1. Sign up free: https://console.apify.com/sign-up (free tier ships with $5/month of credit, enough for ~1,000 post fetches or ~1,000 comment-thread fetches).
2. Generate a token: Console → Settings → Integrations.
3. Drop into .env:

   APIFY_TOKEN=apify_api_...
   

Actors used (all no-cookies, public, no LinkedIn login required):

The thin client lives at lib/apify_client.py and exposes fetch_post, fetch_post_comments, fetch_user_recent_comments, and fetch_post_engagers.

Voice rules (baked into every skill)

1. No em dashes (—), en dashes, or double dashes — biggest AI tell.
2. Use .. as soft pause when mid-sentence rhythm calls for it.
3. Capitalize all personal names, company names, and product names. Lowercase reads as disrespectful.
4. Sentence starts can be lowercase (natural voice), but names inside are always capitalized.
5. Avoid AI vocabulary: leverage, fundamentally, streamline, harness, delve, unlock, foster.
6. Specific numbers beat adjectives — 47% beats significant.
7. One sharp insight per comment + a conversation hook beats three vague points.
8. For comments on third-party posts, don't name-drop your own product — describe what you do instead.
9. LinkedIn posts: 900–1,300 chars sweet spot. Comments: 200–350 chars.
10. Hook lives in the first 210 chars (before "… see more" on mobile).

(Canonical reference, plus comment-specific extensions: references/voice-rules.md. See also references/hook-formulas.md and references/algorithm-heuristics.md.)

How URLs map to URNs

LinkedIn ships three post URN types (the library handles all three):

Comment URLs:

/feed/update/urn:li:activity:POST_ID?commentUrn=urn%3Ali%3Acomment%3A%28activity%3APOST_ID%2CCOMMENT_ID%29

The library decodes the commentUrn fragment and returns both post_urn and comment_id.

Known gotchas

• LinkedIn flattens reply threads to 2 levels. When replying to a reply, pass the top-level comment URN as parentComment, not the reply's URN.
• INSIGHTFUL is NOT a valid Publora reaction type. Use INTEREST instead (the client auto-maps).
• A post URN returned by url_parser may be activity when the canonical URN is actually ugcPost. If posting fails with 404, fall back to resolving via lib.ApifyClient.fetch_post_comments(post_id=...) and read the canonical URN from any existing comment's comment_url.
• Publora schedules comments ~90s in the future by default.

Resources

• Publora API docs — full endpoint reference for the publishing layer
• Apify console — manage actors, tokens, and usage for the read layer
• lib/publora_client.py, lib/apify_client.py — thin Python clients used by every skill

Acknowledgments

Publishing powered by the Publora REST API. Algorithm insights via arXiv 2501.16450 (360Brew) and AuthoredUp 2026 reach data.

LinkedIn Marketing Skills for Claude Code and Codex

10 skills that help Claude Code and Codex 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 Code or Codex:

Codex CLI

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

To test a local clone before publishing changes:

git clone https://github.com/sergebulaev/linkedin-skills.git
cd linkedin-skills
codex plugin marketplace add .
codex plugin add linkedin-skills@linkedin-skills

claude.ai (web)

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.

Claude Desktop (Mac / Windows)

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.

OpenClaw

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.

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 ask Claude Code or Codex for help with LinkedIn. 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

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:

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 Code or Codex 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 Code or Codex:

"Schedule a test LinkedIn post via Publora 24 hours from now: 'testing the API connection — will cancel in dashboard'."

If Publora returns a scheduled-post ID, you're set. Cancel the post in the Publora dashboard before the scheduled time. 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:

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.

Troubleshooting