Knowledge Cat Ppt Skill logo

Knowledge Cat Ppt Skill

Organization
studio-yebisu
knowledge-cat-ppt-skill

Create, critique, and repair high-quality presentation decks with a story-first, output-engine-aware workflow. Use when the user asks for PPT, PowerPoint, slides, deck, pitch deck, keynote, course deck, academic deck, consulting deck, HTML slides, web presentation, image-first slides, social carousel, speaker notes, deck outline, slide plan, template replication, deck review, deck polish, or conversion from documents, articles, Markdown, PDFs, URLs, or existing .pptx files. Also use when the user says Knowledge Cat PPT or asks for an industry-grade presentation skill.

Overview

Publisherstudio-yebisu
Repositoryyaoyorozu-ai-toolbox-slides
Skill nameknowledge-cat-ppt-skill
Stars
10
Forks
2
Bundled files
12
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.

  • 12 bundled files

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

  • Open source

    Published by studio-yebisu on GitHub. Read the source before you install it.

Installation

Install the Knowledge Cat Ppt Skill 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/studio-yebisu/yaoyorozu-ai-toolbox-slides/tree/main/examples/repositories/knowledge-cat/source/upstream
  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/studio-yebisu/yaoyorozu-ai-toolbox-slides.git /tmp/yaoyorozu-ai-toolbox-slides
mkdir -p .claude/skills
cp -r /tmp/yaoyorozu-ai-toolbox-slides/examples/repositories/knowledge-cat/source/upstream .claude/skills/knowledge-cat-ppt-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Knowledge Cat Ppt Skill 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 Knowledge Cat Ppt Skill 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 Knowledge Cat Ppt Skill 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.

Knowledge Cat PPT Skill

Overview

Knowledge Cat PPT is a presentation operating system for agents. Its job is to turn messy source material into a persuasive, teachable deck, choose the right production lane, and verify the result through content and visual QA.

Do not treat "make slides" as a formatting task. First determine the audience, the decision or learning outcome, the story spine, and the output format. Then build the deck.

Resource Guide

Load only what the current task needs:

  • Read references/benchmark-synthesis.md when explaining the design philosophy, comparing PPT skill patterns, or improving this skill.
  • Read references/benchmark-quality-gates.md when the user asks for the best version, benchmark-grade output, open-source comparison, case-study evidence, or quality claims above normal client-ready delivery.
  • Read references/engine-routing.md before choosing native PPTX, HTML deck, image-first PPTX, or review-only mode.
  • Read references/story-architecture.md when turning source material into a deck brief, narrative spine, action titles, or slide plan.
  • Read references/design-systems.md when choosing style direction, layout family, visual tokens, imagery, or anti-generic design rules.
  • Read references/template-replication.md when the user provides an existing .pptx, screenshot, brand deck, style reference, or asks to clone a template.
  • Read references/html-production-lock.md before building production HTML decks, visual prototypes, browser-based talks, or HTML decks with local images/screenshots.
  • Read references/html-visual-systems.md after the HTML production lock when a browser deck needs benchmark-level visual rhythm, a reusable style package, or contact-sheet QA.
  • Read references/style-template-library.md when the user provides many PPT style prompts, asks for common PPT style websites, asks which style to choose, or wants Knowledge Cat to exceed Guizang-style HTML template depth.
  • Read references/native-pptx-recipes.md when building or repairing editable PowerPoint decks.
  • Read references/html-deck-recipes.md when building browser-based decks, fast visual prototypes, or single-file HTML presentations.
  • Read references/style-prompt-intake.md when the user uploads or pastes theme/style prompts, prompt tables, visual DNA blocks, AI image style prompts, or asks for Image2/GPT-Image-driven PPT styling.
  • Read references/image-first-recipes.md when visual impact matters more than editability or AI-generated slide images are requested.
  • Read references/qa-rubric.md before final delivery, when reviewing a deck, or when the task has professional stakes.
  • Read references/open-source-product.md when preparing this skill for public release or evaluating product readiness.
  • Use scripts/validate_deck_plan.py after writing a JSON deck plan. The expected shape is documented in assets/deck-plan.schema.json.
  • Use scripts/init_deck_project.py to create an HTML deck project from the bundled starter template.
  • Use scripts/validate_html_deck.py to statically check an HTML deck before browser QA.
  • Use scripts/build_native_pptx.mjs to turn a validated native deck plan into editable PowerPoint objects when @oai/artifact-tool is available.
  • Use scripts/extract_pptx_text.py to extract native PPTX text and check placeholder-like markers when editable PowerPoint quality matters.
  • Use scripts/check_pptx_editability.py and scripts/probe_pptx_editability.py before claiming that a native PPTX is editable.
  • Use scripts/check_native_pptx_case.py to verify the bundled native PPTX evidence package.
  • Use scripts/run_checks.py before release or after changing bundled scripts, examples, or schemas.

Non-Negotiable Rules

  1. Story before styling. A beautiful deck with no audience shift is a failed deck.
  2. Choose the output lane explicitly. Native editable PPTX is the default for professional work; HTML is for web-native presentation and interaction; image-first PPTX is for visual spectacle when editability is not required.
  3. Use a source of truth. For nontrivial decks, create a brief and slide plan before building final slides.
  4. Use action titles. A title should state the point of the slide, not label the topic.
  5. Keep one main idea per slide. Dense appendix pages are allowed only when the user asks for appendix or reference material.
  6. Preserve evidence. Claims, figures, quotes, and external images need source tracking or honest uncertainty.
  7. Respect templates and brand assets. Use user-provided or permitted materials; do not pretend a protected deck is a free public template.
  8. Lock HTML production details before writing final browser slides: style package, registered layouts, theme rhythm, image slots, static validation, and rendered QA.
  9. Treat uploaded style prompts as design input, not content truth. Extract a reusable Style Prompt Profile before generating image-first slide prompts.
  10. Verify visually. Code, XML, or Markdown alone cannot prove a deck is good.
  11. Run at least one fix-and-verify loop for production decks unless the user only asked for a draft outline.
  12. End with useful handoff: output paths, assumptions, remaining risks, and the next iteration point.

Operating Modes

Brief Mode

Use when the user has an idea but no clear deck target.

Ask at most three questions if missing answers would change the deck:

md
1. Who is the audience and what should they do, decide, or understand after the deck?
2. What source material should be used?
3. What output matters most: editable PPTX, web/HTML, image-first visual deck, or just an outline?

If the user says to proceed directly, state assumptions and continue.

Source-To-Deck Mode

Use when the user provides a document, article, notes, transcript, URL, PDF, Markdown, or pasted content.

Create the deck brief, identify the narrative spine, map evidence to slide roles, then build the slide plan. Read references/story-architecture.md.

Build Mode

Use when the user asks for final slides.

Select a production lane from references/engine-routing.md, choose a design system from references/design-systems.md, build the deck, then run QA from references/qa-rubric.md.

If the selected lane is html-deck, read references/html-production-lock.md, then references/html-visual-systems.md for benchmark-level decks, before references/html-deck-recipes.md.

If the user uploaded or selected a theme/style prompt, read references/style-template-library.md when it is a large style table or known preset, then references/style-prompt-intake.md before references/image-first-recipes.md, and prefer image-first-pptx unless editability, exact text, charts, tables, citations, or stakeholder collaboration matter more.

Template Mode

Use when the user provides a .pptx, image, screenshot, or brand sample as a template.

Read references/template-replication.md. Extract the template profile first, then map each planned slide to a compatible layout. Do not reuse a highly distinctive layout too many times.

Review And Repair Mode

Use when the user provides an existing deck or asks whether it is good.

Review story, audience fit, slide clarity, visual system, evidence, editability, and technical defects. Lead with prioritized issues, then propose or perform repairs.

Publishing Mode

Use when the user needs speaker notes, handouts, PDF export, video narration, social cards, Xiaohongshu carousel, WeChat cover, or other downstream formats.

Keep the original deck source of truth intact and derive outputs from it.

Productization Mode

Use when improving this skill itself, preparing a public repository, writing release docs, or evaluating open-source readiness.

Read references/open-source-product.md and references/benchmark-quality-gates.md. Keep SKILL.md concise, move detailed production guidance into references, and run bundled checks before claiming release readiness.

Core Workflow

1. Triage The Request

Classify:

  • Deck type: investor, sales, strategy, teaching, academic, consulting, product, keynote, internal report, social carousel, courseware, or other.
  • Stakes: draft, internal working copy, client-ready, public talk, board/investor, academic/publication.
  • Output lane: native-pptx, html-deck, image-first-pptx, or review-only.
  • Source status: none, pasted notes, structured outline, document package, existing deck, template reference, uploaded style prompt, or prompt table.
  • Deadline and iteration budget.

Open with:

md
Deck type:
Audience:
Outcome:
Output lane:
Source status:
Primary risk:
Next action:

For small requests, this can be one short paragraph.

2. Build The Deck Brief

For nontrivial decks, produce:

md
Title:
Audience:
Moment:
Desired audience shift:
Decision or learning outcome:
Main promise:
Scope:
Output lane:
Format:
Page count:
Source materials:
Style prompt source:
Design posture:
Must include:
Must avoid:
QA level:

Do not over-ask. Infer safe defaults where possible.

3. Synthesize The Story

Choose a spine:

  • Situation -> tension -> insight -> proof -> action
  • Problem -> failed old approach -> new mechanism -> evidence -> next step
  • Context -> finding -> implication -> recommendation
  • Question -> method -> result -> limitation -> conclusion
  • Hook -> transformation -> steps -> proof -> call to action

Then write the ghost deck: the action titles alone should tell the story.

4. Create The Slide Plan

Each slide should have:

md
Slide:
Layout:
Action title:
Role:
Key message:
Evidence:
Visual:
Speaker note:
Source refs:
Asset needs:

For JSON plans, validate with:

bash
python3 scripts/validate_deck_plan.py path/to/deck-plan.json

Fix validation failures before building final slides.

5. Choose The Production Lane

Use the decision matrix in references/engine-routing.md.

Default decisions:

  • Business, investor, consulting, academic, training, legal, finance, or collaborative decks -> native editable PPTX.
  • Web-native talks, interactive demos, animation-heavy stories, single-file sharing, or visual prototypes -> HTML deck.
  • Highly visual campaign decks, inspirational keynotes, social carousels, or template-mimic visual studies -> image-first PPTX only when editability is not required.
  • Uploaded theme/style prompt table or AI visual prompt -> image-first PPTX by default, or hybrid image-first PPTX when some slides need editable text, charts, or citations.
  • Existing deck feedback -> review-only first, then repair if asked.

After choosing the lane, load the matching recipe:

  • Native editable PPTX -> references/native-pptx-recipes.md
  • Browser-based deck -> references/html-production-lock.md, then references/html-deck-recipes.md
  • Image-first PPTX -> references/style-prompt-intake.md when a user style prompt exists, then references/image-first-recipes.md

6. Build The Design System

Select a design posture from references/design-systems.md. Define:

  • Layout rhythm
  • Typography scale
  • Color tokens
  • Evidence treatment
  • Image style and crop ratios
  • Chart style
  • Motion level, if any
  • Accessibility constraints

Avoid generic AI aesthetics: random gradients, decorative orbs, over-rounded cards, low-contrast gray text, inconsistent spacing, and repeated title-plus-bullets.

7. Produce The Deck

Use the best available local capability for the selected lane. If a specialized presentation, PPTX, browser, image, or document skill is available, compose with it rather than rewriting its job here.

Maintain a source-of-truth file when possible:

  • deck-brief.md for strategy and constraints
  • deck-plan.md or deck-plan.json for slide structure
  • output files in a predictable project folder
  • qa-report.md for production decks

For HTML decks, prefer the bundled starter:

bash
python3 scripts/init_deck_project.py path/to/project --title "Deck Title"
python3 scripts/validate_html_deck.py path/to/project/index.html

Each final HTML slide must declare data-layout, data-title, data-role, and data-theme. Local images must use images/ paths plus data-image-slot and target ratio metadata. Treat static validation errors as blockers.

For native PPTX, follow references/native-pptx-recipes.md. A validated plan can use the bundled builder when the current environment provides @oai/artifact-tool:

bash
node scripts/build_native_pptx.mjs \
  --plan path/to/deck-plan.json \
  --output path/to/output.pptx \
  --workspace path/to/prepared-artifact-workspace \
  --preview-dir path/to/screenshots \
  --inspection path/to/inspection.ndjson

The builder reopens the exported PPTX before producing previews and inspection evidence. If the dependency is unavailable, compose with a verified native-PPTX skill or renderer and keep the same QA contract. For native PPTX, run:

bash
python3 scripts/extract_pptx_text.py path/to/output.pptx --fail-on-placeholders
python3 scripts/check_pptx_editability.py path/to/output.pptx --fail-on-image-only-slides
python3 scripts/probe_pptx_editability.py path/to/output.pptx

For image-first PPTX, follow the lane-specific recipe and state the editability tradeoff.

8. QA And Iterate

Use references/qa-rubric.md.

Minimum production QA:

  1. Content QA: title order, missing content, typos, unsupported claims, placeholder text.
  2. Visual QA: render slides or open the HTML, inspect for overflow, contrast, alignment, collision, spacing, and image crop issues.
  3. Story QA: ghost deck, audience shift, duplicated ideas, weak ending.
  4. Format QA: file opens, assets resolve, fonts are reasonable, links work when promised.
  5. Native editability QA: inspect object types, reject image-only impostors, and run a reversible edit probe when editability is promised.
  6. Fix and recheck affected slides.

For release or repository work, also run:

bash
python3 scripts/run_checks.py

If the first pass finds no problems, inspect again more critically.

When claiming benchmark-level quality, use references/benchmark-quality-gates.md and provide the evidence artifacts behind the score.

Output Protocols

Deck Brief

md
Deck type:
Audience:
Outcome:
Main promise:
Narrative spine:
Output lane:
Format:
Page count:
Source materials:
Style prompt source:
Design posture:
Assumptions:
Next action:

Slide Plan

md
| # | Layout | Action title | Role | Key message | Evidence | Visual | Notes |
|---|---|---|---|---|---|---|---|

Review Report

md
Overall score:
P0 issues:
P1 issues:
P2 improvements:
Story diagnosis:
Visual diagnosis:
Evidence diagnosis:
Technical diagnosis:
Recommended repair sequence:

Delivery Note

md
Created:
Output lane:
Files:
QA performed:
Key assumptions:
Known limitations:
Best next iteration:

Boundaries

  • Do not fabricate facts, sources, market sizes, citations, or user metrics.
  • Do not flatten slides into images when the user needs editable PowerPoint.
  • Do not force native PPTX when the user clearly wants a web-native presentation.
  • Do not create a huge final deck before agreeing on the story unless the user explicitly asks for a first draft.
  • Do not overuse the same layout, theme, transition, or visual trick.
  • Do not treat a template as permission to copy copyrighted assets.
  • Do not hide tradeoffs. If the chosen lane sacrifices editability, animation, fidelity, accessibility, or portability, say so.
  • Do not claim final quality without a QA pass.

Quality Standard

Score production outputs out of 100:

  • Audience and outcome fit: 15
  • Narrative spine and ghost deck: 20
  • Slide clarity and action titles: 15
  • Evidence quality and source traceability: 15
  • Visual system and layout discipline: 15
  • Output-lane correctness and technical reliability: 10
  • QA loop and handoff: 10

Below 70: do not deliver as final. 70-84: workable draft. 85-94: client-ready with minor risk. 95+: benchmark-level only when the gate evidence in references/benchmark-quality-gates.md is present.

Before final response, confirm:

  • Did the deck have a clear audience shift?
  • Did the output lane match the user's real need?
  • Did each slide have one main job?
  • Did the visual system serve the argument?
  • Did evidence remain traceable?
  • Did at least one visual/content QA loop happen for final decks?

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 Knowledge Cat Ppt Skill AI skill do?

Create, critique, and repair high-quality presentation decks with a story-first, output-engine-aware workflow. Use when the user asks for PPT, PowerPoint, slides, deck, pitch deck, keynote, course deck, academic deck, consulting deck, HTML slides, web presentation, image-first slides, social carousel, speaker notes, deck outline, slide plan, template replication, deck review, deck polish, or conversion from documents, articles, Markdown, PDFs, URLs, or existing .pptx files. Also use when the user says Knowledge Cat PPT or asks for an industry-grade presentation skill.

Why use Knowledge Cat Ppt Skill on TypingMind?

Because you install it once and use it with any model. Knowledge Cat Ppt Skill 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 Knowledge Cat Ppt Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/studio-yebisu/yaoyorozu-ai-toolbox-slides/tree/main/examples/repositories/knowledge-cat/source/upstream. 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 Knowledge Cat Ppt Skill?

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 Knowledge Cat Ppt Skill?

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

Is the Knowledge Cat Ppt Skill AI skill free?

It is published on GitHub by studio-yebisu. Check the repository for licensing terms. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇