Lov Any2deck logo

Lov Any2deck

Organization
lovstudio
lov-any2deck

Generate professional slide deck images from content (Markdown, text, URLs). Creates outlines with style instructions, then generates individual slide images. Supports 16 visual styles, CJK/Latin mixed text, branding overlays, and PPTX/PDF export. Use when the user asks to "create slides", "make a presentation", "generate deck", "slide deck", "PPT", "做PPT", "生成幻灯片", "制作演示文稿", or wants to turn content into a visual slide deck.

Overview

Publisherlovstudio
Repositoryskills
Skill namelov-any2deck
Stars
67
Forks
17
Bundled files
37
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.

  • 37 bundled files

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

  • Open source

    Published by lovstudio on GitHub. Read the source before you install it.

Installation

Install the Lov Any2deck 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/lovstudio/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/any2deck .claude/skills/lov-any2deck
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lov Any2deck 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 Lov Any2deck 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 Lov Any2deck 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.

PPT 大师 · PPT Master

Transform content into professional slide deck images.

Usage

bash
/lov-any2deck path/to/content.md
/lov-any2deck path/to/content.md --style sketch-notes
/lov-any2deck path/to/content.md --audience executives
/lov-any2deck path/to/content.md --lang zh
/lov-any2deck path/to/content.md --slides 10
/lov-any2deck path/to/content.md --outline-only
/lov-any2deck  # Then paste content

Script Directory

Agent Execution Instructions:

  1. Determine this SKILL.md file's directory path as SKILL_DIR
  2. Script path = ${SKILL_DIR}/scripts/<script-name>
ScriptPurpose
scripts/merge-to-pptx.tsMerge slides into PowerPoint
scripts/merge-to-pdf.tsMerge slides into PDF
scripts/apply-branding.pyComposite logo(s)/QR onto slides — dual logo, tight-crop, JPG white→alpha (opt-in)

Options

OptionDescription
--style <name>Visual style: preset name, custom, or custom style name
--audience <type>Target: beginners, intermediate, experts, executives, general
--lang <code>Output language (en, zh, ja, etc.)
--slides <number>Target slide count (8-25 recommended, max 30)
--outline-onlyGenerate outline only, skip image generation
--prompts-onlyGenerate outline + prompts, skip images
--images-onlyGenerate images from existing prompts directory
--regenerate <N>Regenerate specific slide(s): --regenerate 3 or --regenerate 2,5,8
--logo <path>Primary brand logo (top-right, skips cover/back-cover)
--logo2 <path>Secondary logo (placed left of primary, optically aligned)
--presentationPresentation mode: strips narration text, keeps only visual anchors

Slide Count by Content Length:

ContentSlides
< 1000 words5-10
1000-3000 words10-18
3000-5000 words15-25
> 5000 words20-30 (consider splitting)

Style System

Presets

PresetDimensionsBest For
blueprint (Default)grid + cool + technical + balancedArchitecture, system design
chalkboardorganic + warm + handwritten + balancedEducation, tutorials
corporateclean + professional + geometric + balancedInvestor decks, proposals
minimalclean + neutral + geometric + minimalExecutive briefings
sketch-notesorganic + warm + handwritten + balancedEducational, tutorials
watercolororganic + warm + humanist + minimalLifestyle, wellness
dark-atmosphericclean + dark + editorial + balancedEntertainment, gaming
notionclean + neutral + geometric + denseProduct demos, SaaS
bold-editorialclean + vibrant + editorial + balancedProduct launches, keynotes
editorial-infographicclean + cool + editorial + denseTech explainers, research
fantasy-animationorganic + vibrant + handwritten + minimalEducational storytelling
intuition-machineclean + cool + technical + denseTechnical docs, academic
pixel-artpixel + vibrant + technical + balancedGaming, developer talks
scientificclean + cool + technical + denseBiology, chemistry, medical
vector-illustrationclean + vibrant + humanist + balancedCreative, children's content
vintagepaper + warm + editorial + balancedHistorical, heritage

Style Dimensions

DimensionOptionsDescription
Textureclean, grid, organic, pixel, paperVisual texture and background treatment
Moodprofessional, warm, cool, vibrant, dark, neutralColor temperature and palette style
Typographygeometric, humanist, handwritten, editorial, technicalHeadline and body text styling
Densityminimal, balanced, denseInformation density per slide

Full specs: references/dimensions/*.md

Auto Style Selection

Content SignalsPreset
tutorial, learn, education, guide, beginnersketch-notes
classroom, teaching, school, chalkboardchalkboard
architecture, system, data, analysis, technicalblueprint
creative, children, kids, cutevector-illustration
briefing, academic, research, bilingualintuition-machine
executive, minimal, clean, simpleminimal
saas, product, dashboard, metricsnotion
investor, quarterly, business, corporatecorporate
launch, marketing, keynote, magazinebold-editorial
entertainment, music, gaming, atmosphericdark-atmospheric
explainer, journalism, science communicationeditorial-infographic
story, fantasy, animation, magicalfantasy-animation
gaming, retro, pixel, developerpixel-art
biology, chemistry, medical, scientificscientific
history, heritage, vintage, expeditionvintage
lifestyle, wellness, travel, artisticwatercolor
Defaultblueprint

Design Philosophy

Decks designed for reading and sharing, not live presentation:

  • Each slide self-explanatory without verbal commentary
  • Logical flow when scrolling
  • All necessary context within each slide
  • Optimized for social media sharing

See references/design-guidelines.md for:

  • Audience-specific principles
  • Visual hierarchy
  • Content density guidelines
  • Color and typography selection
  • Font recommendations

See references/layouts.md for layout options.

File Management

Output Directory

slide-deck/{topic-slug}/
├── source-{slug}.{ext}
├── outline.md
├── prompts/
│   └── 01-slide-cover.md, 02-slide-{slug}.md, ...
├── 01-slide-cover.png, 02-slide-{slug}.png, ...
├── {topic-slug}.pptx
└── {topic-slug}.pdf

Slug: Extract topic (2-4 words, kebab-case). Example: "Introduction to Machine Learning" → intro-machine-learning

Conflict Handling: See Step 1.3 for existing content detection and user options.

Language Handling

Detection Priority:

  1. --lang flag (explicit)
  2. EXTEND.md language setting
  3. User's conversation language (input language)
  4. Source content language

Rule: ALL responses use user's preferred language:

  • Questions and confirmations
  • Progress reports
  • Error messages
  • Completion summaries

Technical terms (style names, file paths, code) remain in English.

Workflow

For the full step-by-step workflow, use references/workflow.md. Keep the main flow in this order:

  1. Setup & analyze: load .lov-skills/lov-any2deck/EXTEND.md when present, save source content, analyze style signals, detect language, choose slide count, and check for existing slide-deck/{topic-slug} output before continuing.
  2. Confirm: use AskUserQuestion for style, audience, slide count, outline review, and prompt review. If custom dimensions are selected, collect texture, mood, typography, and density.
  3. Generate outline: read the selected preset from references/styles/ or combine dimension docs from references/dimensions/, then write outline.md using references/outline-template.md.
  4. Review outline when requested, then generate per-slide prompts under prompts/ using references/base-prompt.md and references/layouts.md.
  5. Review prompts when requested, generate slide images, optionally apply branding with scripts/apply-branding.py, then merge PPTX/PDF with the TypeScript scripts.
  6. Report the output directory, generated slide count, PPTX/PDF paths, style, audience, language, and any partial failures.

Partial workflows (--outline-only, --prompts-only, --images-only, --regenerate) and slide modification procedures are documented in references/workflow.md.

References

FileContent
references/analysis-framework.mdContent analysis for presentations
references/outline-template.mdOutline structure and format
references/modification-guide.mdEdit, add, delete slide workflows
references/content-rules.mdContent and style guidelines
references/design-guidelines.mdAudience, typography, colors, visual elements
references/layouts.mdLayout options and selection tips
references/base-prompt.mdBase prompt for image generation
references/dimensions/*.mdDimension specifications (texture, mood, typography, density)
references/dimensions/presets.mdPreset → dimension mapping
references/styles/<style>.mdFull style specifications (legacy)
references/config/preferences-schema.mdEXTEND.md structure

Notes

  • Image generation: 10-30 seconds per slide
  • Auto-retry once on generation failure
  • Use stylized alternatives for sensitive public figures
  • Maintain style consistency via session ID
  • Step 2 confirmation required - do not skip (style, audience, slides, outline review, prompt review)
  • Step 4 conditional - only if user requested outline review in Step 2
  • Step 6 conditional - only if user requested prompt review in Step 2

Extension Support

Custom configurations via EXTEND.md. See Step 1.1 for paths and supported options.

Runtime context (shared)

运行前读取本 Skill 包的 skill.yaml,由宿主提供 skill-runtime/v1 上下文。字段解析顺序为:当前请求、项目上下文、个人 Preferences、品牌 Profile、通用默认值。

  • 只使用 Manifest 声明的字段;Profile 保存公开品牌事实,Preferences 保存个人工作偏好。
  • required: true 字段缺失时,按 Manifest 的问题配置向用户提出一个聚焦问题;用户明确同意后再保存回答。
  • 报错提供可复制的 context_id、字段路径与来源,诊断内容避开秘密、完整私人路径和原始配置。

通用反馈闭环

用户在 Skill 驱动任务中提出修改意见时,继续当前产物前必须执行:

  1. 先判断意见是 task-specific(仅本次)还是 reusable(可跨任务复用)。
  2. task-specific 只修改当前任务,不改 Skill。
  3. reusable 先确定作用域:领域规则先更新对应 canonical Skill;适用于所有 Skill 的规则先更新共享规范。
  4. 完成规则更新、版本、lint 与分发核验后,再把修改应用到当前任务。
  5. reusable 修改会使此前的“确认”“继续”“发吧”失效;完成当前产物修改和回读后必须停下,等待用户下一步指示,不自动进入发布、提交或其他外部写入。

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 Lov Any2deck AI skill do?

Generate professional slide deck images from content (Markdown, text, URLs). Creates outlines with style instructions, then generates individual slide images. Supports 16 visual styles, CJK/Latin mixed text, branding overlays, and PPTX/PDF export. Use when the user asks to "create slides", "make a presentation", "generate deck", "slide deck", "PPT", "做PPT", "生成幻灯片", "制作演示文稿", or wants to turn content into a visual slide deck.

Why use Lov Any2deck on TypingMind?

Because you install it once and use it with any model. Lov Any2deck 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 Lov Any2deck in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lovstudio/skills/tree/main/skills/any2deck. 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 Lov Any2deck?

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 Lov Any2deck?

As many as you like. As long as a model supports skills, you can use Lov Any2deck with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Lov Any2deck AI skill free?

Yes. It is published on GitHub by lovstudio 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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