pro-ppt

pro-ppt is a skill for Claude Code, Codex from jin-bo/agentao. It costs 204 tokens per session (11,082 once invoked), scanned A, original, MIT.

A presentation-making workflow that turns a speech or slide content into images for polished business-style slides. It first plans each slide and then generates the slide images.

In plain words
What is it for?
Use it to create slides for business, consulting, finance, investor, or corporate presentations. It saves slide plans in Markdown and generated images in the specified workspace folders.
Why use it?
It removes the need to decide the visual layout and image prompt for every slide by hand. It also keeps the colour scheme and visual style consistent across the presentation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/jin-bo/agentao/pro-ppt
Any agent
npx skills add jin-bo/agentao --skill pro-ppt
Clone the repo
git clone --depth 1 https://github.com/jin-bo/agentao

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for pro-ppt

README.md
[![agentmods](https://agentmods.dev/badge/skills/jin-bo/agentao/pro-ppt.svg)](https://agentmods.dev/skills/jin-bo/agentao/pro-ppt)
Your own site
<a href="https://agentmods.dev/skills/jin-bo/agentao/pro-ppt"><img src="https://agentmods.dev/badge/skills/jin-bo/agentao/pro-ppt.svg" alt="Measured on agentmods" height="20"></a>
Per session 204 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 11,082 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00204 $0.11082
Opus 5 $0.00102 $0.05541
Sonnet 5 $0.00041 $0.02216
Haiku 4.5 $0.00020 $0.01108

Measured 6d ago against content hash 8441a5b4ff11, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

pro-ppt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

examples/skills/pro-ppt/SKILL.md · 580 lines

How it starts

The opening of the file, as written. The whole thing — 580 lines — stays where its author put it; the contents beside it link to each section on GitHub.

专业高级感 · 高端商务演示文稿制作指南

总体原则

  • 以**顶级商业编辑(Editorial Premium)高端咨询(McKinsey / BCG / 招股书 / Apple Keynote)**的视觉语言诠释演讲内容
  • 每页图像须忠实传达该页核心信息;构图克制、留白充足、信息分层清晰
  • 全稿风格高度一致;情节转折时仅通过色彩饱和度光照角度的细微变化体现,不破坏统一感
  • 不要出现 血腥、暴力、武器 相关的文字与画面
  • 画面图文结合,可直接用于现场演讲展示,文字必须以排版关系融入构图,禁止悬浮孤立

风格原创合规原则

严禁在提示词中使用任何受版权保护的品牌名、产品名或专有图形,包括但不限于:

  • ❌ 苹果、Apple、iPhone、Tesla、Bloomberg、McKinsey、Goldman 等具体品牌或其标识
  • ❌ 任何受版权保护的字体名(如 SF Pro、Helvetica 商业版)的精确再现

用以下方式描述风格意图(替代品牌名)

  • ❌ "Apple Keynote 风格" → ✅ "极简高端发布会幻灯片风格、巨幅留白、精准对齐、哑光金属质感"
  • ❌ "McKinsey 风格" → ✅ "顶级管理咨询报告风格、严密信息层级、克制配色、几何化数据可视化"
  • ❌ "Bloomberg Terminal 风格" → ✅ "金融终端编辑风格、深色背景、金色高光强调关键指标"

视觉语言系统(必读 · 全稿统一)

本指南定义的「专业高级感」由四个固定维度构成。所有页面都必须严格遵循下述系统,否则会失去统一性与高端感。

1. 色彩系统(Color System)

角色 名称 色值 用途
主色调 极浅灰(Pearl Mist) #F2F2F2 主要文字、信息卡片背景、关键数据数字、图表主体、留白质感
辅助色 A 金属灰(Brushed Metal) #8A8F98 ~ #B8BCC2(哑光金属梯度) 次级文字、分割线、几何结构、装饰性几何体、冷光质感
辅助色 B 高级金(Champagne Gold) #C9A961 / #D4B57A(哑光香槟金,非俗气黄金) 关键指标高亮、重点数据、点睛装饰、获奖/成就标识、勋章质感
背景色 深蓝灰(Midnight Navy) #0F233B 主背景,几乎所有页面都使用,营造深邃专业氛围

配色铁律:

  • 任意一页画面:深蓝灰背景占 60-75%;浅灰元素占 20-30%;金属灰占 5-15%;高级金 ≤ 5%(仅作点睛)
  • 金色不可大面积使用——只用于关键数字、徽章、细线点缀,否则会显得俗气而非高级
  • 浅灰文字必须与深蓝灰背景产生足够对比,可在浅灰下加 5%-10% 不透明度的金属灰渐变以避免「死白」
  • 严禁出现:高饱和的红、绿、蓝、紫等彩色 RGB 原色;卡通配色;荧光色;暖橙色

2. 光照与材质(Lighting & Material)

  • 主光源:来自画面斜上方的柔和顶光,模拟摄影棚布光(Softbox),在金属表面形成温润高光
  • 次光源:背景轻微的体积光(Volumetric Light)/ 雾化光晕,营造空间纵深感
  • 材质语言
    • 哑光金属(Brushed Aluminum)质感的几何体与文字
    • 香槟金的窄边框 / 细线(hairline)
    • 半透明毛玻璃(Frosted Glass)信息卡片
    • 深蓝灰背景带极轻微的颗粒感(Film Grain),避免数字化的廉价平面感
  • 禁止:塑料反光、卡通描边、廉价 3D、过曝高光、廉价镭射效果

3. 排版与版式(Typography & Layout)

  • 网格系统:采用 12 列基础网格,左右各 1 列空白边距,所有元素严格对齐基线
  • 字体语言(在提示词中描述质感,不指定具体商业字体):
    • 标题:极细 / 中粗的现代无衬线字体(Modern Sans-Serif),字距宽松(letter-spacing 较大),呈现「编辑大字报」气质
    • 关键数据:超粗的 Display 字体或细衬线(Didone 风格的 thin serif),用于「巨型数字」呈现
    • 正文与图注:极细无衬线,字号克制
  • 版式偏好
    • 大量留白(白银比例 / 黄金比例)
    • 标题与内容之间常用一条细金色 hairline 分隔
    • 信息以「卡片 / 模块 / 表格」形式呈现,而非段落散文
    • 角标(如 01 / 12§ 02CHAPTER ONE)出现在画面左上或右下,强化「报告页」气质

Read the full file on GitHub · 580 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 580 lines · 204 tokens per session scan A 8441a5b4ff11

Subscribe to this mod's changes

pro-ppt is a skill published in the GitHub repository jin-bo/agentao (100 stars, last pushed today), licensed MIT. It adds 204 tokens to every session and 11,082 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens