linkedin-post-adapter

linkedin-post-adapter is a skill for Claude Code, Codex from Livus-AI/Skills-MCP. It costs 52 tokens per session (710 once invoked), scanned A, original, MIT.

A writing tool that turns a Twitter thread into a professional LinkedIn post. LinkedIn is a professional social network, while a Twitter thread is a series of connected posts.

In plain words
What is it for?
Repurposing Twitter content for LinkedIn, creating business-to-business posts, and adding a newsletter link in the first comment. Optional industry hashtags can also be included.
Why use it?
It removes the need to rewrite short, casual posts for a business-focused audience. It also changes the call to action so readers are encouraged to discuss the topic.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Repurposing Twitter content for LinkedIn, creating business-to-business posts, and adding a newsletter link in the first comment. Optional industry hashtags can also be included.

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Install with agentmods
npx agentmods add skills/livus-ai/skills-mcp/linkedin-post-adapter
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Livus-AI/Skills-MCP --skill linkedin-post-adapter
Clone the repo
git clone --depth 1 https://github.com/Livus-AI/Skills-MCP

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for linkedin-post-adapter

README.md
[![agentmods](https://agentmods.dev/badge/skills/livus-ai/skills-mcp/linkedin-post-adapter/github.svg)](https://agentmods.dev/skills/livus-ai/skills-mcp/linkedin-post-adapter)
Your own site
<a href="https://agentmods.dev/skills/livus-ai/skills-mcp/linkedin-post-adapter"><img src="https://agentmods.dev/badge/skills/livus-ai/skills-mcp/linkedin-post-adapter/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for linkedin-post-adapter

Your own site · 80×15
<a href="https://agentmods.dev/skills/livus-ai/skills-mcp/linkedin-post-adapter"><img src="https://agentmods.dev/badge/skills/livus-ai/skills-mcp/linkedin-post-adapter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 710 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.00710
Opus 5 $0.00026 $0.00355
Sonnet 5 $0.00010 $0.00142
Haiku 4.5 $0.00005 $0.00071

Measured 12d ago against content hash b7ae3878e181, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

linkedin-post-adapter scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/linkedin-post-adapter/SKILL.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LinkedIn Post Adapter Skill

Transform a Twitter thread into a polished, professional LinkedIn post optimized for B2B engagement and discussion.

Required Inputs

  • Twitter Thread - Output from twitter-thread-generator skill
  • Newsletter Link - URL for the first comment CTA
  • Relevant Hashtags (optional) - 3-5 industry hashtags

Key Adaptations

Element Twitter LinkedIn
Tone Casual, punchy Professional, insightful
Length Short tweets 2-3 paragraphs
Hook Bold/provocative Benefit-oriented
CTA In final tweet In first comment
Engagement Retweets Comments/discussion

Post Structure

Main Post

[Professional Hook - benefit-oriented opening]

[Paragraph 1: Core narrative and context - expand on the story]

Here are the key takeaways:

• [Takeaway 1 - from thread insights]
• [Takeaway 2 - from thread insights]  
• [Takeaway 3 - from thread insights]

[Paragraph 2: Why this matters - strategic implications]

This trend is reshaping how [industry] operates. Those who adapt early will have a significant advantage.

What's your take on this? How is your team approaching [topic]?

#hashtag1 #hashtag2 #hashtag3

First Comment (Post Immediately After)

For a deeper analysis and weekly insights on [topic], check out my free newsletter.

We break down the most important developments every week.

Link: [Newsletter URL]

Writing Guidelines

  • Professional but not stiff - conversational expertise
  • Use bullet points for scanability
  • End with a question to drive comments
  • 3-5 relevant hashtags - not more
  • CTA in first comment - maximizes reach (LinkedIn algorithm)

Hook Adaptations

Twitter Hook LinkedIn Adaptation
"AI won't take your job..." "The professionals thriving in 2025 share one thing in common..."
"7 AI tools that..." "After testing 50+ AI tools, these 7 are actually worth your time:"
"Everyone says X. They're wrong." "The conventional wisdom about X is costing companies millions:"

Read the full file on GitHub · 105 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 105 lines · 52 tokens per session scan A b7ae3878e181

Subscribe to this mod's changes

linkedin-post-adapter is a skill published in the GitHub repository Livus-AI/Skills-MCP (2 stars, last pushed 3mo ago), licensed MIT. It adds 52 tokens to every session and 710 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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