Ppt Complex Diagram Collab logo

Ppt Complex Diagram Collab

Community
Sven-LI-sankyuu
ppt-complex-diagram-collab

Use when collaborating with humans to produce publication-grade complex diagrams in editable PPT, especially for system architecture, dataflow, and user-journey visuals that require shape-level connector validation and reproducible outputs.

Overview

PublisherSven-LI-sankyuu
Repositorypresentation-skills
Skill nameppt-complex-diagram-collab
Stars
177
Forks
23
Bundled files
6
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.

  • 6 bundled files

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

  • Open source

    Published by Sven-LI-sankyuu on GitHub. Read the source before you install it.

Installation

Install the Ppt Complex Diagram Collab 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/Sven-LI-sankyuu/presentation-skills/tree/main/old/ppt-complex-diagram-collab
  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/Sven-LI-sankyuu/presentation-skills.git /tmp/presentation-skills
mkdir -p .claude/skills
cp -r /tmp/presentation-skills/old/ppt-complex-diagram-collab .claude/skills/ppt-complex-diagram-collab
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ppt Complex Diagram Collab 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 Ppt Complex Diagram Collab 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 Ppt Complex Diagram Collab 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 Complex Diagram Collab

归档说明

  • 本 skill 在仓库中已经归档到 old/ppt-complex-diagram-collab/,后续主线能力统一迁移到 ppt-polished-deck-collab/。
  • 这里保留的价值主要是复杂图、connector 校验和视觉经验,不再作为主线持续扩展入口。

概览

把“业务讲清楚 + 图可复用 + 论文可交付”作为同一个任务完成。 优先交付图包(planning + mermaid + editable PPT + 校验结果),不要只交单张图。

执行目录约定

  • 以下命令默认在 old/ppt-complex-diagram-collab/ 目录内执行(即本 SKILL.md 同级目录)。
  • 若你从其他目录执行,请自行补齐前缀路径。

工作流

按下面顺序执行,避免返工。

  1. 先确认环境基线
  • 先读取 references/tested_environment.md。
  • 至少确认 Python、python-pptx、Node/npm、mermaid-cli 可用。
  • 不强制新建 conda 环境:如果现有环境能安装并稳定运行所需包,直接复用即可;需要隔离再新建临时环境。
  • 如果当前环境和基线差异较大,先记录差异再开始出图,避免“图能生成但不可复现”。
  1. 先锁定交付规格
  • 明确主图用途:论文主图、答辩图、工程文档图。
  • 明确输出形态:*.md(含 mermaid)、*.mmd(可选)、*.pptx(可编辑)。
  • 明确可编辑定义:
    • 如果使用 connector:拖动节点时连线仍然绑定,不是“视觉上像连着”;
    • 如果不使用 connector(分层架构图常见):用箭头/卡片表达层级递进,此时连线校验期望 connectors=0。
  • 先选视觉语法(分层架构图 vs 数据流/因果图),避免把两张图硬塞一张图。
  1. 拆分图集而不是硬塞一张图
  • 先给图清单:总览分层图 + 关键执行链路图 + 用户视角流程图。
  • 给每张图编号(如 Fig00~Fig09)并定义“读者问题 -> 图回答什么”。
  • 使用 references/figure_planning_template.md 组织范围和边界。
  1. 先做可讨论版本(mermaid)
  • 在一个文档里集中维护图集与解释,保证评审快。
  • 保持节点命名稳定,避免后续 PPT 版无法对齐。
  • 用脚本批量渲染 SVG/PDF/PNG,确保论文与汇报都能复用。
  1. 再做可编辑版本(PPT)
  • 用 python-pptx 直接画 shape(必要时才画 connector),不要仅插入 PNG。
  • 分层架构图(Fig00)推荐默认用 Layer Card + 递进箭头,避免 hairball;数据流图(Fig01)再用 connector。
  • 如果使用 connector:
    • 连接线必须使用 begin_connect()/end_connect() 粘连到具体 shape;
    • 优先连接“业务节点框”,不要连接 lane/cluster 外框;
    • 控制 edge budget(参考视觉/连线策略文档)。
  • 如果不使用 connector:
    • 箭头应表达“层级递进/主方向”,不要用长 chevron 文案当装饰;
    • 仍然建议运行连线校验,确认 connectors=0。
  1. 强制做连线校验
  • 运行 scripts/check_pptx_connectors.py 校验:
    • 每条 connector 同时存在 stCxn 和 endCxn;
    • 连接的 shape id 必须可解析到文本节点;
    • 不允许粘到被禁止前缀(如 Lane )节点。
  • 可选:如果这张图预期必须存在 connector,用 --min-connectors 防止“意外生成了 0 条连线”。
  • 用 references/ppt_connector_debug.md 做人工复核。
  1. 迭代时只改关键差异
  • 用户反馈“线条拖动会散”时,先定位具体哪条边,不做大重画。
  • 优先修连接点索引映射和目标 shape 绑定关系。
  • 每次迭代后重新生成 PPT 并复跑校验脚本。

交付清单

一次完整交付至少包含:

  • 图集说明文档(图编号、用途、约束)。
  • mermaid 源和批量渲染脚本。
  • 可编辑 pptx 生成脚本。
  • 连线校验脚本输出(命令 + 结果)。
  • 视觉方案与连线策略说明(建议作为附录或 style_spec.md),保证可复用与可复现。

快速命令

bash
# 1) 生成可编辑 PPT(示例)
python <diagram_dir>/build_editable_pptx.py

# 2) 校验连线是否真绑定
python scripts/check_pptx_connectors.py \
  --pptx <diagram_dir>/pptx/<name>.pptx \
  --slide 10 \
  --forbid-prefix "Lane " \
  --min-connectors 1

资源使用规则

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 Ppt Complex Diagram Collab AI skill do?

Use when collaborating with humans to produce publication-grade complex diagrams in editable PPT, especially for system architecture, dataflow, and user-journey visuals that require shape-level connector validation and reproducible outputs.

Why use Ppt Complex Diagram Collab on TypingMind?

Because you install it once and use it with any model. Ppt Complex Diagram Collab 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 Ppt Complex Diagram Collab in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Sven-LI-sankyuu/presentation-skills/tree/main/old/ppt-complex-diagram-collab. 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 Ppt Complex Diagram Collab?

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 Ppt Complex Diagram Collab?

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

Is the Ppt Complex Diagram Collab AI skill free?

It is published on GitHub by Sven-LI-sankyuu. 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 👇