mckinsey-market-resear…
End-to-end playbook for producing a top-tier, McKinsey-style market-research deck (HTML page-turning presentation + print-ready PDF) for a brand or product…
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
$ npx -y skills add norahe0304-art/30x-mckinsey-research-deck --skill mckinsey-deck --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/mckinsey-deckContext preview
The summary Claude sees to decide when to auto-load this skill.
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
name: mckinsey-deck description: > 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.) allowed-tools: - Read - Write - Edit - Bash - Glob
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.
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:
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.
Headline = a full-sentence conclusion (the takeaway), never a topic label.
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.
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.
# 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-*.pngCheck 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).
If you list URLs (sources/appendix), wrap each in `<a href="<full-url>">…</a>` — Chrome's `--p
一条指令,产出一份敢被挑战的麦肯锡级市场研究 deck。 这是一个 Claude Code Skill(安装进 Claude Code 会话里用,不是独立运行的 CLI 工具)——不需要单独的 API key,研究和 deck 生成全部发生在 Claude Code 会话内部(复用会话自带的模型访问),不是你在终端里单独调用的脚本。内置 adversarially verified numbers、15 套麦肯锡方法论的可执行工作流、多 agent pipeline。
End-to-end playbook for producing a top-tier, McKinsey-style market-research deck (HTML page-turning presentation + print-ready PDF) for a brand or product…