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Mckinsey Deck

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norahe0304-art
mckinsey-deck

Turn any content into a top-tier McKinsey-style deck — a 1280×720 page-turning HTML presentation that also prints to a clean per-slide PDF. Use when the user wants a "McKinsey-style deck / presentation", a polished slide deck or PDF from notes/content, an executive/board/investor deck, or to "make slides / a deck / a PDF report" with a premium consulting look. (For full market research with sizing + competitor + business case, use mckinsey-market-research-deck instead.)

Overview

Publishernorahe0304-art
Repository30x-mckinsey-research-deck
Skill namemckinsey-deck
Stars
55
Forks
6
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by norahe0304-art on GitHub. Read the source before you install it.

Installation

Install the Mckinsey Deck 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/norahe0304-art/30x-mckinsey-research-deck/tree/master/skills/mckinsey-deck
  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/norahe0304-art/30x-mckinsey-research-deck.git /tmp/30x-mckinsey-research-deck
mkdir -p .claude/skills
cp -r /tmp/30x-mckinsey-research-deck/skills/mckinsey-deck .claude/skills/mckinsey-deck
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mckinsey Deck 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 Mckinsey Deck 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 Mckinsey Deck 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.

McKinsey-Style Deck (the style + engine skill)

Build a research-grade-looking, page-turning deck from content the user gives you. Reviewed on screen as an HTML presentation; shared as a print-clean PDF. The whole engine is one file — assets/deck_engine.py — copy it into the project and compose build().

This skill owns the canonical engine. mckinsey-market-research-deck (and any future deck skill) consumes assets/deck_engine.py from HERE — engine fixes land in this file only, never in a project-local or sibling-skill fork. One engine, zero drift.

How to use

  1. Copy assets/deck_engine.py into the working dir. Set BRAND (the footer line) and OUT_HTML.
  2. Compose the deck inside build() using the renderers (below). Feed them the user's content directly, or load from a JSON if the content is structured.
  3. Render + export:
    bash
    python3 deck_engine.py
    "/Applications/Google Chrome.app/Contents/MacOS/Google Chrome" --headless --disable-gpu \
      --no-pdf-header-footer --print-to-pdf="Deck.pdf" "Deck.html"
    (Windows/Linux: swap the Chrome path for chrome/google-chrome.)
  4. QC (below), fix, re-render, then deliver.

Renderers (all in deck_engine.py)

  • cover(title_html, subtitle) — navy hero (uses product-images/cover-hero.png if present), title + one subtitle.
  • answer_slide(title, deck, governing, pillars, src) — the executive-summary page (Pyramid Principle: answer first). One-sentence governing thought + 3–4 pillar conclusions, each optionally with a serif key stat. Place right after the cover; reading only the headlines from here to the end must form one persuasive essay (horizontal logic).
  • divider(no, title, points) — full-navy section break; big sky-blue number; optional duotone image (divider-<no>.png).
  • heroes([(num, label), ...]) — 4-up serif stat strip.
  • prose_slide(title, deck, themes, src, cols=2, note=None) — "bold theme + paragraph" blocks (the McKinsey prose page). themes=[(heading, paragraph_html), ...].
  • essay_slide(title, deck, lead, paras, src, side=None) — flowing two-column prose + optional side rail.
  • table_slide(title, deck, columns, rows, src, note=None, fill=True, bold_keys=(), extra=None) — navy-header table, uniform row heights (header 34px / rows 52px, never stretched); bold_keys highlights total rows; extra= takes a content block (e.g. heroes([...])) to fill a sparse page by composition.
  • decision_slide(page, src) — renders a structured exhibit (buildup/breakdown/scenarios + assumptions + READ).
  • donut_block(...), bars_chart(...), heatmap_block(...) — titled chart blocks for a page's side rail (charts ride beside their analysis; never alone on a page); charts_slide(...) for the rare full-canvas exhibit. Low-level: donut_svg(...), heatmap hcell(...).
  • sources_register(url_set, selected_rows, src) — the numbered, clickable source appendix.
  • render(slides) — assembles the page-turning HTML and prints the div-balance check.

Headline = a full-sentence conclusion (the takeaway), never a topic label.

Hard design laws (never violate)

  • No eyebrow/kicker labels — no small letter-spaced ALL-CAPS tags above titles or on the cover.
  • Cover is minimal: title + one italic subtitle only. No KPI band, no date, no method block.
  • Action-title headlines — the headline states the conclusion.
  • Notes pinned to a uniform bottom (margin-top:auto) on every page.
  • Nothing overlaps the footer. .pad reserves bottom clearance.
  • Fill by composition, not by stretching. Essay/prose type auto-scales across 3 tiers by content length. Table row heights are uniform deck-wide (header 34px / rows 52px) and never stretch — fill a sparse table page via table_slide(..., extra=heroes([...])) or more rows. If a page is still thin at the top tier, add content — never inflate type or rows.
  • No mid-word truncation — use clipw(), never raw [:n].
  • Flat — no shadows/bevels (navy cover/divider are the only image-shadow exception).
  • Images — clean cutout on pure white, no shadow, blended via mix-blend-mode:multiply; every image gets an italic caption. Cover/divider images: anchored bottom-right, height:100% (never >100%, or the PDF clips the subject), left-edge gradient mask so the square dissolves into navy.

Palette (baked into the engine CSS)

navy #051C2C · blue #1F6FB2 · sky #5AA9E0 · ink #23272E · muted #7B8593 · hairline #E3E6EB. Headlines Georgia; body Inter. Color is rationed: navy structure + grays, blue/sky as small accents.

QC before delivery (always self-run)

bash
# structure — must be 0, or an unclosed div breaks pagination
python3 -c "h=open('Deck.html').read();print('div diff:',h.count('<div')-h.count('</div>'))"
pdfinfo Deck.pdf | grep Pages
# visual — render every page and eyeball
pdftoppm -png -r 92 Deck.pdf _q   # then look at _q-*.png

Check each page: no footer overlap · no mid-word "…metal o" cuts · <30% whitespace · notes at a uniform bottom · images blended with captions · cover has no eyebrow/date. Fix, re-render, re-check.

Browser caching trap: open-ing an already-open HTML only refocuses the stale tab — verify by rendering the PDF, and tell the user to hard-refresh (Cmd+Shift+R).

Make links clickable

If you list URLs (sources/appendix), wrap each in <a href="<full-url>">…</a> — Chrome's --print-to-pdf turns them into clickable PDF link annotations (verify: the PDF bytes contain /URI).

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 Mckinsey Deck AI skill do?

Turn any content into a top-tier McKinsey-style deck — a 1280×720 page-turning HTML presentation that also prints to a clean per-slide PDF. Use when the user wants a "McKinsey-style deck / presentation", a polished slide deck or PDF from notes/content, an executive/board/investor deck, or to "make slides / a deck / a PDF report" with a premium consulting look. (For full market research with sizing + competitor + business case, use mckinsey-market-research-deck instead.)

Why use Mckinsey Deck on TypingMind?

Because you install it once and use it with any model. Mckinsey Deck 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 Mckinsey Deck in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/norahe0304-art/30x-mckinsey-research-deck/tree/master/skills/mckinsey-deck. 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 Mckinsey Deck?

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 Mckinsey Deck?

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

Is the Mckinsey Deck AI skill free?

Yes. It is published on GitHub by norahe0304-art 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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