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Linkedin

Organization
hyperfx-ai
linkedin

Publish and manage LinkedIn content via the Hyper MCP — text posts, article / link previews, document and PDF posts, organization (company page) posts, and AI-generated text-to-carousel posts. Use when the user wants to post on LinkedIn, share an article on LinkedIn, post to a LinkedIn company page, upload a PDF / document to LinkedIn, or build a LinkedIn carousel from text.

Overview

Publisherhyperfx-ai
Repositorymarketing-skills
Skill namelinkedin
Stars
107
Forks
21
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by hyperfx-ai on GitHub. Read the source before you install it.

Installation

Install the Linkedin AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hyperfx-ai/marketing-skills/tree/main/skills/linkedin
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hyperfx-ai/marketing-skills.git /tmp/marketing-skills
mkdir -p .claude/skills
cp -r /tmp/marketing-skills/skills/linkedin .claude/skills/linkedin
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Linkedin in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Linkedin on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Linkedin is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

LinkedIn

Skill for publishing to LinkedIn through the LinkedIn integration exposed by the Hyper MCP.

Out of scope — defer to other skills

RequestSend them to
Instagram post / Reel / Storyinstagram
TikTok organic postingtiktok
TikTok ad campaigntiktok-ads
Meta (Facebook / Instagram) adsmeta-ads
Google Ads campaigngoogle-ads
Amazon Sponsored Products campaignamazon-ads

Requirements

If linkedin_text_posts_create is not found, the integration to connect is LinkedIn.

How to run the tools in this skill

Every tool in this skill is named by its canonical tool name. Run it with the call your surface gives you:

SurfaceFind a toolRun it
Hyper chatCall the tool by its name; search_tools(queries=["<provider> <action>"]) shows its parameters<name>(...)
MCP client (Claude, Cursor, Codex, ChatGPT)search("<what you want to do>"), then describe("<name>")call_read("<name>", {...}), call_write or call_destructive: the one that describe names in call_with
Hyper CLIhyperai search "<what you want to do>", then hyperai describe <name>hyperai call <name> --json '{...}'

If a tool is not found: in Hyper chat, find its toolkit id with discover_toolkits and pass it to enable_toolkit. On an MCP client or the CLI, tell the user which integration to connect in Hyper.

Tool surface

ToolPurpose
linkedin_text_posts_createStandard member or organization text post; also article / link posts via the article fields.
linkedin_organization_posts_createPost explicitly as a company page (when you already know organization_id).
linkedin_document_posts_createPDF / document post — LinkedIn renders pages as a swipeable document.
linkedin_carousels_create_from_textAI text-to-carousel pipeline — generates slides + assembles a PDF + publishes as a document post.

Posting Rules

  1. Use linkedin_text_posts_create for standard member or organization posts.
  2. Use linkedin_organization_posts_create when the user explicitly wants to post as a company page and you already know the organization_id.
  3. Use linkedin_document_posts_create for PDF / document uploads. LinkedIn renders PDF pages as a swipeable document post.
  4. Use linkedin_carousels_create_from_text when the user wants a text-to-carousel workflow driven by AI-generated slides.

Article / Link Posts

Do not rely on LinkedIn to scrape Open Graph metadata for API-created posts.

For reliable article posts:

  • Provide article_url.
  • Prefer explicit article_title, article_description, and thumbnail_url.
  • If those fields are omitted, the backend may derive them from the shared page metadata, but explicit values are still more reliable.

Use this shape when editing or preparing a LinkedIn article post:

python
linkedin_text_posts_create(
    text="Caption text",
    article_url="https://example.com/article",
    article_title="Explicit preview title",
    article_description="Explicit preview description",
    thumbnail_url="https://example.com/thumbnail.jpg",
    organization_id="123456789",  # optional
)

Document and Carousel Posts

LinkedIn carousels are implemented as document posts backed by a PDF.

Native PDF flow

Use linkedin_document_posts_create when you already have a PDF URL or stored file ID:

python
linkedin_document_posts_create(
    text="Caption text",
    title="Deck title",
    document_url="https://example.com/deck.pdf",
    organization_id="123456789",  # optional
)

Text-to-carousel flow

Use linkedin_carousels_create_from_text when the user wants the system to build the carousel from a block of source text:

python
linkedin_carousels_create_from_text(
    text_content="Source content for the slides",
    title="Carousel title",
    caption="LinkedIn caption",
    num_slides=4,
    style="professional",
    color_scheme="blue",
    organization_id="123456789",  # optional
)

The current implementation:

  • Parses the source text into slide content.
  • Generates a single grid image with an image model.
  • Splits the grid into individual slide images.
  • Assembles a PDF.
  • Publishes the PDF as a LinkedIn document post.
  • Returns the live post URL — present this to the user to confirm the carousel is live.

Supported slide counts are 4, 6, and 9.

Manual Slide Editing

The current LinkedIn carousel pipeline is PDF-based. It does not provide a first-class live canvas editing loop before publish.

If a user wants manual refinement:

  1. Generate the carousel assets first.
  2. Review or edit the generated slide images / PDF externally.
  3. Post the final PDF with linkedin_document_posts_create.

Do not promise an in-product editable canvas workflow unless the tool is actually available in the current environment.

Organization Posting

When posting to a company page:

  • If you don't know the organization_id, call linkedin_managed_pages_list() first — it returns all company pages the connected account can post to, with their IDs.
  • Use linkedin_organizations_posts_list_detailed(organization_id=...) to preview recent posts before publishing — avoids accidental duplicates.
  • Pass organization_id to whichever posting tool you're using.
  • Expect LinkedIn org posting permissions to matter.
  • If a post fails with a permissions error, verify that the authenticated account can post to that organization.

Failure Modes & Recovery

  • Article preview is empty / wrong. LinkedIn ignored the scraped metadata. Re-call linkedin_text_posts_create with explicit article_title, article_description, and thumbnail_url.
  • Permission error on organization post. Confirm with the user that their LinkedIn account has page-posting permission for the target organization_id.
  • linkedin_carousels_create_from_text returned an unexpected slide count. Only num_slides of 4, 6, or 9 are supported.
  • Document post fails with an invalid URL. The document_url must be a directly-fetchable PDF (no auth, no HTML redirect page).

Frequently asked questions

What does the Linkedin AI skill do?

Publish and manage LinkedIn content via the Hyper MCP — text posts, article / link previews, document and PDF posts, organization (company page) posts, and AI-generated text-to-carousel posts. Use when the user wants to post on LinkedIn, share an article on LinkedIn, post to a LinkedIn company page, upload a PDF / document to LinkedIn, or build a LinkedIn carousel from text.

Why use Linkedin on TypingMind?

Because you install it once and use it with any model. Linkedin is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Linkedin in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hyperfx-ai/marketing-skills/tree/main/skills/linkedin. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Linkedin?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Linkedin?

As many as you like. As long as a model supports skills, you can use Linkedin with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Linkedin AI skill free?

Yes. It is published on GitHub by hyperfx-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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