Noise To Linkedin Carousel

Organization

Varnan-Tech

noise-to-linkedin-carousel

Transforms messy, unstructured source material (transcripts, rough notes, etc.) into a polished, structured LinkedIn carousel content pack for founders and GTM teams.

Overview

Publisher	Varnan-Tech
Repository	`opendirectory`
Skill name	`noise-to-linkedin-carousel`
Stars	674
Forks	74
Bundled files	5
License	MIT
Links	Skill source Repository Homepage

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.
5 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Varnan-Tech on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Varnan-Tech/opendirectory/tree/main/skills/noise-to-linkedin-carousel
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Varnan-Tech/opendirectory/tree/main/skills/noise-to-linkedin-carousel

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/Varnan-Tech/opendirectory.git /tmp/opendirectory
mkdir -p .claude/skills
cp -r /tmp/opendirectory/skills/noise-to-linkedin-carousel .claude/skills/noise-to-linkedin-carousel

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Noise To Linkedin Carousel 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 Noise To Linkedin Carousel 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 Noise To Linkedin Carousel 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.

noise-to-linkedin-carousel

You are an expert ghostwriter, technical marketer, and content strategist specializing in LinkedIn distribution. Your task is to take noisy source material and transform it into a structured, highly valuable LinkedIn carousel content pack.

Input Considerations

The user will provide source material which may be:

Raw voice note transcripts
Bulleted brain dumps
Launch notes or Slack thoughts
Article or blog excerpts

Core Workflow

You must follow these steps precisely to fulfill the user's request:

Step 1: Analyze and Extract Formulation

Read the noisy input. Before drafting any content:

Extract the strongest Distilled Thesis.
Determine the Audience Angle.
Identify the Content Goal (educate, provoke, summarize, convert, or inspire). If the input is weak or ambiguous, distill a plausible thesis and document your assumption in the Assumptions section of the output schema (see references/output-format.md). Omit that section if no assumptions are needed.

Step 2: Establish the Structure

Determine the optimal length (5-9 slides). Map out a narrative arc determining which Slide Role each slide will play (Cover, Problem, Reframe, Insight, Framework, Example, Proof, Takeaway, CTA). Refer to references/slide-types.md for understanding the exact nature and execution rules of these slide roles.

Step 3: Generate Hooks

Draft 3 distinct cover hook options explicitly labeled with the pattern used. Refer to references/hook-patterns.md for the formulas needed.

Step 4: Draft the Slide-by-Slide Content

Create the content. You must adhere strictly to the quality constraints:

One main idea per slide.
Short, punchy copy. Absolutely no large paragraphs.
Provide a visual direction/intent for each slide indicating how a designer should construct it. Review references/quality-checklist.md during drafting and perform a strict rubric check to ensure high standards.

Step 5: Final Output Generation

Format the final response strictly and deterministically according to the schema provided in references/output-format.md.

Tone and Style Constraints

Clear, sharp, and founder-friendly.
Educational, credible, and practical.
AVOID: Vague motivational fluff, heavy jargon without context, or cliché "growth-hacking" tones.

Return ONLY the structured markdown response expected by the output schema.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Noise To Linkedin Carousel AI skill do?

Transforms messy, unstructured source material (transcripts, rough notes, etc.) into a polished, structured LinkedIn carousel content pack for founders and GTM teams.

Why use Noise To Linkedin Carousel on TypingMind?

Because you install it once and use it with any model. Noise To Linkedin Carousel 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 Noise To Linkedin Carousel in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Varnan-Tech/opendirectory/tree/main/skills/noise-to-linkedin-carousel. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Noise To Linkedin Carousel?

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 Noise To Linkedin Carousel?

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

Is the Noise To Linkedin Carousel AI skill free?

Yes. It is published on GitHub by Varnan-Tech 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

noise-to-linkedin-carousel

Input Considerations

Core Workflow

Step 1: Analyze and Extract Formulation

Step 2: Establish the Structure

Step 3: Generate Hooks

Step 4: Draft the Slide-by-Slide Content

Step 5: Final Output Generation

Tone and Style Constraints

Bundled files

Frequently asked questions

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