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Humanize Ppt

Community
podo
humanize-ppt

Presentation planner and checker for agent-made decks. Turns raw material into an audience-state-transfer outline with per-page image, diagram, or video decisions, hands a production brief to a downstream renderer, then runs a capped checkup on the rendered deck. It never renders slides itself.

Overview

Publisherpodo
Repositorydesign-agent-skills
Skill namehumanize-ppt
Stars
27
Forks
3
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 podo on GitHub. Read the source before you install it.

Installation

Install the Humanize Ppt 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/podo/design-agent-skills/tree/main/skills/humanize-ppt
  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/podo/design-agent-skills.git /tmp/design-agent-skills
mkdir -p .claude/skills
cp -r /tmp/design-agent-skills/skills/humanize-ppt .claude/skills/humanize-ppt
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Humanize Ppt 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 Humanize Ppt 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 Humanize Ppt 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.

humanize-ppt

Catalogue stub — full skill: LearnPrompt/humanize-ppt

Decision tree

  1. Is the full skill already installed?

    • Global: f=~/.agents/skills/humanize-ppt/SKILL.md; [ -f "$f" ] && ! grep -q "^das:" "$f" && echo "installed" || echo "pointer"
    • Project: f=.agents/skills/humanize-ppt/SKILL.md; [ -f "$f" ] && ! grep -q "^das:" "$f" && echo "installed" || echo "pointer"
    • installed → the skill is installed as humanize-ppt, invoke it and proceed
    • pointer → go to step 2
  2. Detect scope, then install:

    bash
    [ -e ~/.agents/skills/humanize-ppt ] && echo "global" || echo "project"

    Global:

    bash
    npx skills add LearnPrompt/humanize-ppt --skill humanize-ppt -g -y

    Project:

    bash
    npx skills add LearnPrompt/humanize-ppt --skill humanize-ppt -y

    Claude Code: send a command as a chat message starting with ! to run it without leaving the conversation.

Heads-up

  • Requires: A downstream renderer skill (it never renders slides itself): guizang-ppt-skill for Chinese decks, frontend-slides for English HTML decks
  • License: MIT (LICENSE file; GitHub reports it as non-standard)
  • Download size: ~40 MB.

Invoke after install

  • Skill name: humanize-ppt
  • Run it before rendering (brief mode) and again after rendering with the rendered deck as input (checkup mode)
  • Trigger phrases: "humanize ppt", "presentation outline director", "audience state transfer outline", "presentation checkup"

What it does

Treats a deck as an audience state-transfer artifact rather than an information container. From notes, transcripts, documents, or links it writes a deck brief, an AST outline, a slide plan with a per-page media decision (photo, system diagram, short process clip, or nothing), speaker intent, and a style brief for the next agent. After a downstream skill renders the deck, a checkup pass compares each rendered page to its outline page, flags pages that can only be looked at rather than spoken from, and writes fix instructions, for up to three rounds before handing back to a human. It owns the story and the check, not the visuals.

When NOT to use

  • You only want one good-looking template page with no outline or checkup → use a renderer directly: html-ppt, frontend-slides, kami, or guizang-ppt
  • Markdown-driven developer decks → use slidev-skill or marp-slides
  • Linting slide quality for Marp decks → use marp-slide-quality

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 Humanize Ppt AI skill do?

Presentation planner and checker for agent-made decks. Turns raw material into an audience-state-transfer outline with per-page image, diagram, or video decisions, hands a production brief to a downstream renderer, then runs a capped checkup on the rendered deck. It never renders slides itself.

Why use Humanize Ppt on TypingMind?

Because you install it once and use it with any model. Humanize Ppt 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 Humanize Ppt in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/podo/design-agent-skills/tree/main/skills/humanize-ppt. 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 Humanize Ppt?

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 Humanize Ppt?

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

Is the Humanize Ppt AI skill free?

Yes. It is published on GitHub by podo 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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