
Baoyu-slide-deck generates professional slide deck images from markdown content by creating structured outlines with customizable style instructions and then rendering individual slides as images. It serves users who need to quickly transform written content into visual presentations, supporting multiple styles (blueprint, corporate, minimal, etc.), target audiences, and languages. The skill solves the problem of manually designing slides by automating the outline-to-image pipeline while allowing control over visual presentation, slide count, and content complexity.
$ npx -y skills add jimliu/baoyu-skills --skill baoyu-slide-deck --agent claude-codeInstalls into .claude/skills of the current project.
Decks are designed for reading and sharing (self-explanatory slides, logical scroll flow, social-media-friendly), not live presentation — this drives every layout and density decision.
When this skill prompts the user, follow this tool-selection rule (priority order):
AskUserQuestion, request_user_input, clarify, ask_user, or any equivalent.Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes.
Resolve the image backend in this order:
preferred_image_backend in EXTEND.md names a backend available now → use it. ask means ask every run.auto, unset, or the pinned backend is unavailable), first match wins:
imagegen skill is in your available skills → you are in Codex and MUST use it: Skill with skill: "imagegen", passing the prompt file's content plus output path and aspect ratio. It outranks non-native skills such as baoyu-image-gen.codex exec (codex-imagegen): no native imagegen, but the codex CLI is on PATH with an active codex login → baoyu-image-gen --provider codex-cli (preferred), or the bundled wrapper if baoyu-image-gen is unavailable. Load references/codex-imagegen.md only for this branch.GenerateImage → use it (outranks non-native skills). It has no aspect-ratio parameter, so state the aspect ratio / dimensions in the description prompt; it saves to a tool-managed location, so copy the file to the expected output path (e.g., outputs/.../NN-xxx.png). Reference images go in reference_image_paths.image_generate) → use it the same way.baoyu-image-gen) → use it.⛔ Raster only: never substitute SVG, HTML/CSS, canvas, or other code-based rendering for a raster image, even for diagram-like content. If no raster backend resolves, go to step 4.
⛔ No bitmap text patching: never use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other overlay to cover, rewrite, erase, stroke, or replace slide titles, bullets, or any other text inside an already generated slide image. Regenerate from a corrected prompt, simplify the slide's on-image text, or ask the user which imperfect candidate to keep.
Prompt file (hard): before invoking any backend, write each image's full, final prompt to its own file under prompts/ (NN-slide-[slug].md) and pass that file (or its content) to the backend. It is the reproducibility record and lets you switch backends without rewriting prompts.
Change the pinned backend via ## Changing Preferences below. Tool names above are examples; use the local equivalent in other runtimes.
After every prompt file for the current generation group is saved and verified, generate slide images in batches by default:
generation_batch_size slide images at a time (default 4). An explicit request in the current message (e.g. --batch-size 4, "并行4张一起生成") overrides EXTEND.md.Rules:
Default behavior: confirm before generation.
EXTEND.md defaults as recommendation inputs only. None of them authorizes skipping confirmation.Respond in the user's language across questions, progress reports, error messages, and the completion summary. Keep technical tokens (style names, file paths, code) in English.
{baseDir} = this SKILL.md's directory. Resolve ${BUN_X}: prefer bun; else npx -y bun; else suggest brew install oven-sh/bun/bun.
| Script | Purpose |
|---|---|
scripts/merge-to-pptx.ts | Merge slides into PowerPoint |
scripts/merge-to-pdf.ts | Merge slides into PDF |
| Option | Description |
|---|---|
--style <name> | Preset (see Presets below), custom, or custom style name |
--audience <type> | beginners / intermediate / experts / executives / general |
--lang <code> | Output language (en, zh, ja, ...) |
--slides <N> | Target slide count (8-25 recommended, max 30) |
--ref <files...> | Reference images applied per slide (style / palette / composition / subject) |
--batch-size <n> | Temporary slide image generation batch size for this run. Default: generation_batch_size from EXTEND.md, otherwise 4. Clamp to 1-8. |
--outline-only | Stop after outline |
--prompts-only | Stop after prompts (skip image generation) |
--images-only | Skip to Step 7; requires existing prompts/ |
--regenerate <N> | Regenerate specific slide(s): 3 or 2,5,8 |
Each preset combines four dimensions (texture / mood / typography / density). If the user picks "Custom dimensions" in Round 1, Round 2 asks one question per dimension (copy in references/confirmation.md).
| Preset | Dimensions | Best For |
|---|---|---|
blueprint (Default) | grid + cool + technical + balanced | Architecture, system design |
chalkboard | organic + warm + handwritten + balanced | Education, tutorials |
corporate | clean + professional + geometric + balanced | Investor decks, proposals |
minimal | clean + neutral + geometric + minimal | Executive briefings |
sketch-notes | organic + warm + handwritten + balanced | Educational, tutorials |
hand-drawn-edu | organic + macaron + handwritten + balanced | Educational diagrams, process explainers |
watercolor | organic + warm + humanist + minimal | Lifestyle, wellness |
dark-atmospheric | clean + dark + editorial + balanced | Entertainment, gaming |
notion | clean + neutral + geometric + dense | Product demos, SaaS |
bold-editorial | clean + vibrant + editorial + balanced | Product launches, keynotes |
editorial-infographic | clean + cool + editorial + dense | Tech explainers, research |
fantasy-animation | organic + vibrant + handwritten + minimal | Educational storytelling |
intuition-machine | clean + cool + technical + dense | Technical docs, academic |
pixel-art | pixel + vibrant + technical + balanced | Gaming, developer talks |
scientific | clean + cool + technical + dense | Biology, chemistry, medical |
vector-illustration | clean + vibrant + humanist + balanced | Creative, children's content |
vintage | paper + warm + editorial + balanced | Historical, heritage |
Per-preset specs: references/styles/<preset>.md. Preset → dimension mapping: references/dimensions/presets.md.
| Dimension | Options | Purpose |
|---|---|---|
| Texture | clean, grid, organic, pixel, paper | Background treatment |
| Mood | professional, warm, cool, vibrant, dark, neutral, macaron | Color temperature |
| Typography | geometric, humanist, handwritten, editorial, technical | Headline/body styling |
| Density | minimal, balanced, dense | Information per slide |
Full per-dimension specs: references/dimensions/*.md.
Pick the first row whose signal keywords appear in the source; fall back to blueprint.
| Signals in source | Preset |
|---|---|
| tutorial, learn, education, guide, beginner | sketch-notes |
| hand-drawn, infographic, diagram, process, onboarding | hand-drawn-edu |
| classroom, teaching, school, chalkboard | chalkboard |
| architecture, system, data, analysis, technical | blueprint |
| creative, children, kids, cute | vector-illustration |
| briefing, academic, research, bilingual | intuition-machine |
| executive, minimal, clean, simple | minimal |
| saas, product, dashboard, metrics | notion |
| investor, quarterly, business, corporate | corporate |
| launch, marketing, keynote, magazine | bold-editorial |
| entertainment, music, gaming, atmospheric | dark-atmospheric |
| explainer, journalism, science communication | editorial-infographic |
| story, fantasy, animation, magical | fantasy-animation |
| gaming, retro, pixel, developer | pixel-art |
| biology, chemistry, medical, scientific | scientific |
| history, heritage, vintage, expedition | vintage |
| lifestyle, wellness, travel, artistic | watercolor |
| Source length | Recommended slides |
|---|---|
| < 1000 words | 5-10 |
| 1000-3000 words | 10-18 |
| 3000-5000 words | 15-25 |
| > 5000 words | 20-30 (consider splitting) |
User-supplied images guide style, palette, layout, or subject.
Intake via --ref <files...> or file paths / pasted images in conversation:
{slide-deck-dir}/refs/NN-ref-{slug}.{ext}Usage modes (per reference):
| Usage | Effect |
|---|---|
direct | Pass the file to the backend as a reference image for each slide |
style | Extract style traits (line treatment, texture, mood) and append to every slide's prompt body |
palette | Extract hex colors and append to every slide's prompt body |
Record refs in each slide's prompt frontmatter:
references:
- ref_id: 01
filename: 01-ref-brand.png
usage: direct
At generation time, verify files exist. If usage: direct and the backend accepts refs (e.g., baoyu-image-gen --ref), pass the file on every slide. Otherwise embed extracted style/palette traits in the prompt text.
slide-deck/{topic-slug}/
├── source-{slug}.{ext}
├── outline.md
├── prompts/NN-slide-{slug}.md
├── NN-slide-{slug}.png
├── {topic-slug}.pptx
└── {topic-slug}.pdf
Slug: 2-4 words, kebab-case, extracted from topic. "Introduction to Machine Learning" → intro-machine-learning.
Backup rule (all steps): if a file about to be written already exists, rename it to <name>-backup-YYYYMMDD-HHMMSS.<ext> first.
- [ ] Step 1: Setup & analyze
- [ ] Step 2: Confirmation ⚠️ REQUIRED (Round 1; Round 2 only if "Custom dimensions")
- [ ] Step 3: Generate outline
- [ ] Step 4: Review outline (conditional)
- [ ] Step 5: Generate prompts
- [ ] Step 6: Review prompts (conditional)
- [ ] Step 7: Generate images
- [ ] Step 8: Merge to PPTX/PDF
- [ ] Step 9: Output summary
1.1 Load EXTEND.md — check these paths in order; first hit wins:
| Path | Scope |
|---|---|
.baoyu-skills/baoyu-slide-deck/EXTEND.md | Project |
${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-slide-deck/EXTEND.md | XDG |
$HOME/.baoyu-skills/baoyu-slide-deck/EXTEND.md | User home |
If found, read, parse, and print a summary (style / audience / language / review / generation batch size). If not, proceed with defaults — first-time setup is not blocking for this skill. Schema: references/config/preferences-schema.md.
1.2 Analyze content — follow references/analysis-framework.md: classify content, detect language, note signals for style selection, estimate slide count from length (see the Slide Count Heuristic in Style System above), generate topic slug. Save source as source.md (honor backup rule if one exists).
1.3 Check existing output ⚠️ REQUIRED before Step 2. If slide-deck/{topic-slug}/ exists, ask how to proceed — four options (regenerate outline / regenerate images / backup and regenerate / exit), verbatim copy in references/confirmation.md.
Save findings to analysis.md: topic, audience, signals, recommended style and slide count, language detection.
Hard gate per the Confirmation Policy: Steps 3+ wait for the user's answer here unless the current request explicitly opts out ("直接生成" or equivalent).
Round 1 (always) — batch five questions in one AskUserQuestion call: style, audience, slide count, review-outline?, review-prompts?. Verbatim options in references/confirmation.md.
Show before the questions: content type + topic, detected language, recommended style (from signals), recommended slide count (from length).
Round 2 (only if "Custom dimensions" in Round 1) — batch four questions: texture, mood, typography, density. Verbatim options in references/confirmation.md. The four answers replace the preset.
After confirmation: update analysis.md with final choices and store skip_outline_review / skip_prompt_review flags from Q4/Q5.
Resolve style: preset → references/styles/{preset}.md; custom dimensions → combine files in references/dimensions/. Build STYLE_INSTRUCTIONS from the resolved style, apply confirmed audience + language + slide count, follow references/outline-template.md, and save as outline.md.
Stop here if --outline-only. Skip Step 4 if skip_outline_review.
Display a slide-by-slide table (# | Title | Type | Layout) along with total count and resolved style. Ask: proceed / edit outline first / regenerate — verbatim in references/confirmation.md.
On "Edit outline first", tell the user to edit outline.md and ask again when ready. On "Regenerate outline", return to Step 3.
For each slide in outline:
references/base-prompt.mdSTYLE_INSTRUCTIONS from the outline (don't re-read the style file)Layout: is specified, include guidance from references/layouts.mdprompts/NN-slide-{slug}.md (backup rule applies)Stop here if --prompts-only. Skip Step 6 if skip_prompt_review.
Display the prompts index (# | Filename | Slide Title) and ask: proceed / edit prompts first / regenerate — verbatim in references/confirmation.md. Branches mirror Step 4.
codex-imagegen, follow references/codex-imagegen.md (n=1 per call, so slide batches dispatch one wrapper call per slide).prompts/NN-slide-{slug}.md exists (hard requirement).slides-{topic-slug}-{timestamp} — pass to the backend only if it supports sessions.## Batch Generation Policy. Backup rule applies to PNG files before dispatch. Report progress as Generated X/N. Retry only failed items once before reporting an error.--regenerate N jumps to this step for the named slides only. --images-only starts here with existing prompts.
${BUN_X} {baseDir}/scripts/merge-to-pptx.ts <slide-deck-dir>
${BUN_X} {baseDir}/scripts/merge-to-pdf.ts <slide-deck-dir>
Slide Deck Complete!
Topic: [topic]
Style: [preset or "custom: texture+mood+typography+density"]
Location: [directory]
Slides: N
- 01-slide-cover.png
- ...
- NN-slide-back-cover.png
Outline: outline.md
PPTX: {topic-slug}.pptx
PDF: {topic-slug}.pdf
| Action | How |
|---|---|
| Edit | Update prompts/NN-slide-{slug}.md first, then --regenerate N |
| Add | Create new prompt at position, generate image, renumber subsequent NN (slugs unchanged), update outline.md, re-merge |
| Delete | Remove PNG + prompt, renumber subsequent, update outline.md, re-merge |
Always update the prompt file before regenerating the image (prompts are the source of truth). Only NN changes on renumber; slugs stay stable.
Text correction policy:
See references/modification-guide.md for full details.
references/design-guidelines.md — audience, typography, color selectionreferences/content-rules.md — content and style rulesEXTEND.md lives at the first matching path in Step 1.1.
references/config/preferences-schema.md.preferred_image_backend: auto — default; runtime-native tool wins, falls back to the only installed backend, asks only if multiple non-native are present.preferred_image_backend: codex-imagegen — pin to Codex's built-in.preferred_image_backend: baoyu-image-gen — pin to the baoyu-image-gen skill.preferred_image_backend: ask — confirm backend every run.generation_batch_size: 4 — default number of slide images to render concurrently when the backend/runtime supports batch or parallel generation.preferred_style: blueprint, preferred_audience: experts, language: zh.Sponsors