dmccreary/claude-skills/linkedin-carousel-generator
Claude Code and agent skill by dmccreary/claude-skills
- community
Checking that the SKILL.md file is still in the repository.
Generates a 13-slide LinkedIn carousel (a "document post" — PPTX/PDF) that showcases an intelligent textbook's key features, with real screenshots, mascot art, and metrics pulled from the project. Use when the user wants a LinkedIn slideshow/carousel/document post for a textbook, as opposed to linkedin-announcement-generator which produces post *text* only.
Install
npx vskill@latest install dmccreary/claude-skills/linkedin-carousel-generatorSKILL.md
LinkedIn Carousel Generator
Generates a 13-slide LinkedIn carousel — LinkedIn calls this a "document post" — that visually walks a reader through what makes an intelligent textbook worth exploring. Unlike linkedin-announcement-generator (which writes the post's caption text), this skill produces the artifact itself: a square, mobile-readable slide deck the reader swipes through in their feed, built from the project's real metrics, mascot art, and screenshots.
When to Use This Skill
Use this skill when the user says things like:
- "Make a LinkedIn carousel/slideshow for this textbook"
- "Create a LinkedIn document post"
- "I want a slide deck I can upload to LinkedIn"
Do not use this skill when the user wants only the caption/post text — use linkedin-announcement-generator for that (the two are often used together: carousel as the attached document, announcement text as the post copy, with the carousel referenced instead of a bare link).
Do not use textbook-to-presentation-generator for this — that skill builds a 25-35 slide lecture deck for live classroom delivery with speaker notes. This skill builds a much shorter, image-heavy, no-speaker-notes deck meant to be read silently on a phone in a feed.
Prerequisites
- Node.js installed, with
pptxgenjsinstalled locally in the output directory
(npm install pptxgenjs)
- An intelligent textbook project with:
mkdocs.yml(site name, description, theme palette)docs/about.md(the "Why This Book" narrative)docs/learning-graph/book-metrics.json(canonical metrics — see
book-installer's bk-generate-book-metrics if missing)
docs/img/mascot/with the character sheet and pose PNGs (seebook-installer's
learning-mascot guide if the project has no mascot yet)
docs/license.mdanddocs/img/license.png- At least one MicroSim under
docs/sims/, and (ideally) a learning-graph viewer
MicroSim (commonly docs/sims/graph-viewer/)
~/.local/bin/bk-capture-screenshotavailable (installed bymicrosim-utils) for the two
screenshots this skill needs
- Python 3 with Pillow (
pip install pillow) for cropping the learning-graph screenshot
If any prerequisite is missing, tell the user which one and point at the skill that creates it rather than improvising a substitute (e.g. don't hand-draw a learning graph image if book-metrics.json and a real graph viewer exist).
The 13 Slides
| # | Slide | Content source | Image source | |
|---|---|---|---|---|
| 1 | Cover | mkdocs.yml site_name / site_description | docs/img/cover.png (if present) + mascot welcome.png | |
| 2 | Why This Book | docs/about.md → "Why This Intelligent Textbook" section | mascot thinking.png or welcome.png, floated left | |
| 3 | Learning Graph | docs/learning-graph/book-metrics.json (concepts, taxonomy categories, edges) + docs/learning-graph/index.md | Zoomed crop of the graph-viewer MicroSim screenshot, floated right | |
| 4 | Coverage Summary | Chapter count from book-metrics.json + 4-6 standout chapter titles from mkdocs.yml nav | Big-number treatment, no image needed | |
| 5 | Engagement Strategy | The "Read → Run → Modify" Skulpt-lab cycle (or the project's equivalent hands-on loop) from CLAUDE.md / CONTENT-GENERATION-GUIDELINES.md | 3-icon row, deliberately NOT a wall of text | |
| 6 | Mascot Summary | Mascot character sheet (docs/img/mascot/character-sheet.md) | Grid of pose PNGs with a 2-4 word role label under each | |
| 7 | MicroSim Count | microsims count from book-metrics.json + one-sentence definition of "MicroSim" | Screenshot of one flagship MicroSim (confirm which one with the user) | |
| 8 | Supplementary Content | glossaryTerms, faqs, quizQuestions, references counts from book-metrics.json | 4-icon stat row | |
| 9 | License | docs/license.md license type | docs/img/license.png + note on customizing colors/logo/mascot for another school | |
| 10 | Adaptivity | How Claude Skills add whole new chapters/lessons consistent with the existing book (course-description → learning-graph → chapter generators) | Simple pipeline diagram (3-4 boxes) | |
| 11 | Continuous Enrichment | Forward-looking: agents proposing content/MicroSim variants, measured via analytics/A/B testing, phrased as a capability the framework supports, not a claim of an existing automated pipeline | Icon-based, light touch | |
| 12 | Summary of Benefits | A recap checklist of the strongest points from slides 2-11 — the 5-6 most compelling facts, each condensed to a single bolded phrase (e.g. "450 concepts, 0 dependency violations", "31 interactive MicroSims", "Free & open source") | none — checklist pattern, no image needed | |
| 13 | Closing CTA | Site URL, GitHub repo URL, "free & open source" | mascot celebration.png, dark background matching slide 1 |
This mapping is a strong default, not a rigid template — if the project lacks one of these elements (no stories, zero equations, etc.), drop or substitute a slide rather than showing a zero. See references/content-sourcing.md for the exact extraction commands for every slide.
Slide 12 exists to close the loop before the CTA: by slide 11 the reader has seen ten different facts in ten different visual styles — slide 12 pulls the single strongest claim out of each of slides 2-11 into one scannable list, so a reader who only skims gets the whole pitch in five seconds before hitting the ask on slide 13. Pick the best fact per slide, not every fact — this slide fails if it turns back into a wall of text.
Workflow
Step 1: Gather Source Material
Read, in parallel:
mkdocs.yml—site_name,site_description,site_url,repo_url, and
theme.palette.primary / theme.palette.accent (drives every slide's color scheme)
docs/about.md— pull the "Why This Book" / "Why This Intelligent Textbook" sectiondocs/learning-graph/book-metrics.json— the canonical metrics object (same file
linkedin-announcement-generator and readme-generator use — keep numbers consistent across all three artifacts)
docs/img/mascot/character-sheet.md— name, species, and the pose tabledocs/learning-graph/color-config.json(if present) — taxonomy category colors, used as
a small legend on the learning-graph slide
docs/license.md— license type and URLmkdocs.ymlnav — chapter list, to hand-pick 4-6 standout titles for slide 4
If book-metrics.json is missing or stale, regenerate it first (bk-generate-book-metrics) rather than estimating numbers.
Step 2: Capture the Two Required Screenshots
Learning graph (slide 3): Run bk-capture-screenshot against the graph-viewer MicroSim (commonly docs/sims/graph-viewer/) at a large window size so labels are legible when cropped:
The full-graph screenshot shows all concepts at once — too dense to read at slide/thumbnail size. Crop to a readable cluster of 15-25 nodes that shows concept labels and a spread of taxonomy colors, using scripts/crop-screenshot.py:
Adjust the --box left,top,right,bottom coordinates by opening the full screenshot first — don't guess blindly. If no crop region looks clean (e.g. the graph is too sparse or labels overlap everywhere), fall back to asking the user to manually pan/zoom the live viewer in a browser and take their own screenshot.
Flagship MicroSim (slide 7): Ask the user which MicroSim best represents the book if it isn't obvious (prefer one with strong visuals — turtle graphics, a chart, a network — over a plain form-based one), then:
Step 3: Confirm the Outline Before Generating
Before writing any slide code, show the user:
- The 13-slide plan with the specific numbers it will display (e.g. "38 chapters, 450
concepts, 31 MicroSims, 338 glossary terms")
- Which chapters you picked to highlight on slide 4
- Which MicroSim you picked for slide 7
- Which 5-6 facts you picked for the slide 12 benefits recap
This is a quick sanity check, not a full design review — the numbers are objective (pulled from book-metrics.json), but the chapter/MicroSim/recap picks are subjective and worth a 10-second confirmation before building 13 slides around them.
Step 4: Set Up the pptxgenjs Project
Use a square 10in x 10in slide (pptx.defineLayout({name:'SQUARE', width:10, height:10})) — LinkedIn document posts render best at 1:1 on mobile feeds. If the user prefers the taller 4:5 format some carousels use, use width:8, height:10 instead; confirm with the user only if they express a preference, otherwise default to square.
Step 5: Build Each Slide
Read references/slide-patterns.md for the nine reusable pptxgenjs slide patterns (title/ cover, mascot-aside, image-aside, big-numbers, icon-row, pose-grid, badge-callout, checklist recap, closing CTA) and references/content-sourcing.md for exactly which field feeds which slide. Map the 13 slides in the table above onto these patterns — several slides reuse the same pattern with different content (e.g. slides 2, 3, 9 are all variants of "image on one side, text on the other").
Design rules — LinkedIn carousels are read on a phone, not projected:
- No more than ~25 words of body text per slide (this is a stricter cap than a lecture deck)
- Minimum 18pt body text, 36pt+ for headlines — small text is illegible in the LinkedIn
in-feed thumbnail
- One idea per slide, always
- Dark background (primary color) for slides 1 and 13 only — bookends the deck; slides 2-12
stay light/white for readability and print/PDF friendliness
- Use the project's actual
theme.palette.primary/accentfrommkdocs.yml, not generic
blues
Step 6: Generate and Verify
- Run the Node.js script to produce the
.pptx - Confirm exactly 13 slides were produced
- Open each slide (or export slide 1, 3, 6, 7, 12, and 13 as PNGs) and visually check that no
text overflows its box and that images aren't stretched or pixelated
- Report slide count and file size to the user
Step 7: Prepare for LinkedIn Upload
LinkedIn's document-post uploader (the icon in "Start a post" that looks like a page/document, distinct from the photo icon) accepts .pptx, .ppt, .pdf, .doc, and .docx directly — no PDF conversion is required. If the user wants a smaller file or to strip editable metadata before sharing, offer to convert with LibreOffice if it's installed:
Tell the user LinkedIn will also ask for a document title shown above the carousel in the feed — suggest a short, benefit-led title (e.g. "13 Things That Make This Python Textbook Different"), not the book's formal title.
Remind the user of the same rule from linkedin-announcement-generator: the post caption should not contain the external site link (LinkedIn suppresses reach on posts with links in the body) — but a URL printed as text on slide 13 of the document itself is fine, since it's not a clickable hyperlink in the post body. If they're also posting caption text, hand off to linkedin-announcement-generator and tell them to paste the site URL as the first comment, same as always.
Output
This is the start of the file. Read the full SKILL.md on GitHub.
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/archived/linkedin-carousel-generator/SKILL.md
Popularity
- Repository stars
- 91
- Repository forks
- 12
- 7-day trend score
- 23
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
Embed badge
[](https://verified-skill.com/skills/dmccreary/claude-skills/linkedin-carousel-generator)