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Gemini Carousel

CommunityPopular
charlie947
gemini-carousel

Generate a branded slide-by-slide LinkedIn carousel using Gemini. Takes source content, builds a design brief, waits for approval, then outputs per-slide image generation prompts. 1080x1350 vertical format. Use this skill whenever the user says "carousel", "build a carousel", "turn this into a carousel", "gemini carousel", or wants multi-slide LinkedIn content. Always includes an approval gate between brief and image generation.

Overview

Publishercharlie947
Repositorysocial-media-skills
Skill namegemini-carousel
Stars
3.6K
Forks
836
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 charlie947 on GitHub. Read the source before you install it.

Installation

Install the Gemini Carousel 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.
  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/charlie947/social-media-skills.git /tmp/social-media-skills
mkdir -p .claude/skills
cp -r /tmp/social-media-skills/skills/gemini-carousel .claude/skills/gemini-carousel
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gemini 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 Gemini 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 Gemini 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.

Gemini Carousel

Codex and Claude runtime

  • Use this skill in Codex or Claude with the tools actually available in the current task. AskUserQuestion examples describe the questions, not a required API: use an available question tool within its limits, or ask in chat. Reuse answers and source material already supplied.
  • Work in the user-selected project. Read its about-me.md, voice.md and relevant brand files before personalised work. Confirm the intended author if files conflict or contain starter defaults. Ask for missing facts or run voice-builder; never inherit the maintainer's identity, accounts or private files.
  • Resolve bundled references/ relative to this skill folder. For an explicitly requested profile refresh, read and update the canonical about-me.md, voice.md or newsletter-voice.md in place, preserving unrelated user facts and rules. Consumers must reread those canonical files. Use a new filename only for new deliverables that would collide with unrelated existing files. Installation alone never starts an interview or writes files. Do not write persistent learnings unless requested.
  • Use supplied evidence first. Verify external claims through available search/source tools when needed. If a source or integration is unavailable, name the missing capability and offer supplied text/export input. Never invent facts, first-person experience, metrics or a successful tool run.
  • Connect only services needed for the chosen route through the user's existing account. Never print credentials or overwrite connections. Drafting, saving and reviewing do not authorise publishing, sending messages or changing accounts.

Visual completion state

This skill's image prompts are prompt-ready, not generated or visually reviewed assets. Keep its named Gemini workflow unless the user requests another generator. A missing image service does not block writing a prompt. When images are supplied or generated, open and inspect each export at full size and feed size (about 360px wide, 320px for thumbnails). Check exact copy, dimensions, clipping, legibility, brand colours, font appearance, logos and reference fidelity. Fix and re-inspect failed exports. Record any unavailable export or inspection as pending. An image prompt or raster export is not an editable design file.

CRITICAL: Auto-start on load

When this skill triggers, go straight to Step 1. Do not summarise.

Step 1. Gather inputs

Ask:

Paste the content you want in the carousel. A post, section of a newsletter, research notes, or a framework all work.

Wait for the content, then call AskUserQuestion:

json
[
  {
    "question": "Brand style?",
    "header": "Style",
    "multiSelect": false,
    "options": [
      {"label": "Pull from brand-kit.md", "description": "Use the colours and typography in my project brand file"},
      {"label": "I will type brand colours", "description": "I will paste hex codes and font preferences"},
      {"label": "Suggest for me", "description": "Pick a palette and typography based on the content"}
    ]
  },
  {
    "question": "Number of slides?",
    "header": "Slides",
    "multiSelect": false,
    "options": [
      {"label": "6 slides", "description": "Concise, fast read"},
      {"label": "8 slides", "description": "Standard carousel length"},
      {"label": "10 slides", "description": "Deep-dive carousel"}
    ]
  }
]

Step 2. Build the design brief

Analyse the content and produce a slide-by-slide brief with:

  • Slide 1 (Cover): hook, large bold text, visual direction
  • Slides 2 to N-1 (Body): one idea per slide, concise copy and a specific illustration or diagram that explains it. Preserve all required items and source qualifications; propose more slides if needed.
  • Slide N (Ending): useful conclusion or next action, with a CTA only for a real user-approved offer or link

For each slide include:

  • Slide number
  • Headline (max 8 words)
  • Body text (max 15 words)
  • Visual suggestion (icon, colour block, illustration, diagram)

Tell the user:

Here is the design brief. Tell me what to change, or say "generate" when you are happy.

Wait for approval. Do not proceed until the user explicitly approves.

Step 3. Output per-slide prompts

Once approved, output one Gemini image generation prompt per slide, each in its own code block, numbered clearly.

Every prompt follows this structure:

Act as an expert graphic designer. Create a LinkedIn carousel slide at 1080x1350 pixels (4:5 aspect ratio).

Brand style:
- Primary colour: [HEX]
- Secondary colour: [HEX]
- Accent colour: [HEX]
- Typography: [bold industrial headline font, clean geometric body font]
- Aesthetic: modern, authoritative, high contrast

Slide [N of M]: [slide purpose]

Content:
- Headline: "[headline text]"
- Body: "[body text]"
- Visual element: [specific visual suggestion]

Layout instructions:
- [Headline placement and size]
- [Body placement and size]
- [Visual placement]
- [Background treatment]

Constraints:
- Vertical 4:5 aspect ratio at exactly 1080x1350 pixels
- No watermarks, no logos unless specified above
- Maintain visual consistency with the other slides in the set

Tell the user:

Paste each prompt into a new Gemini chat with Create Image enabled and Nano Banana selected. Generate slides one at a time for maximum control over consistency.

Step 4. Offer one-shot alternative

After the per-slide prompts, offer:

Want a single combined prompt that generates the full carousel in one shot? Faster but less visual consistency. Say "combine" and I will rewrite.

Rules

  • Always gate on user approval of the brief before outputting image prompts.
  • 1080x1350 pixels per slide. No other aspect ratio.
  • Target 15 words of body text per slide, but never remove a required fact to hit the target. Split the content during briefing when it needs more space.
  • Keep the brand style identical across every slide prompt so the set looks like one carousel.
  • Cover slide (1) and CTA slide (last) must be visually distinct from body slides.
  • Never use em dashes.
  • British English unless voice.md specifies otherwise.
  • If brand-kit.md exists in the project, read it and use its exact hex codes and typography choices.

Frequently asked questions

What does the Gemini Carousel AI skill do?

Generate a branded slide-by-slide LinkedIn carousel using Gemini. Takes source content, builds a design brief, waits for approval, then outputs per-slide image generation prompts. 1080x1350 vertical format. Use this skill whenever the user says "carousel", "build a carousel", "turn this into a carousel", "gemini carousel", or wants multi-slide LinkedIn content. Always includes an approval gate between brief and image generation.

Why use Gemini Carousel on TypingMind?

Because you install it once and use it with any model. Gemini 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 Gemini Carousel in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/charlie947/social-media-skills/tree/main/skills/gemini-carousel. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Gemini 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 Gemini Carousel?

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

Is the Gemini Carousel AI skill free?

Yes. It is published on GitHub by charlie947 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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