explaingit

woyin2024/lengyi-ppt-agent-team

13Audience · pm founderComplexity · 2/5ActiveLicenseSetup · easy

TLDR

Chinese-language multi-agent prompt pack with six Ming-court roles (coordinator, researcher, fact-checker, architect, visual, PPT engineer) that build slide decks as HTML.

Mindmap

mindmap
  root((ppt-agent-team))
    Inputs
      User brief
      Approval gates
      Tool list
    Outputs
      Research report
      Slide outline
      Generated images
      HTML deck
    Use Cases
      Auto build slide decks
      Run multi-agent on any platform
      Reuse prompts across runtimes
    Tech Stack
      Markdown
      AGENTS prompts
      Web search tools
      Image gen models
      guizang-ppt-skill

Things people build with this

USE CASE 1

Generate research-backed HTML slide decks from a one-line user brief

USE CASE 2

Run a six-agent court flow (Neige, Jinyiwei, Dongchang, Hanlin, Gongbu, Zhizaoju) on MiniMax or Codex

USE CASE 3

Cross-verify slide content against at least two sources before approving the deck

USE CASE 4

Reuse the AGENTS.md prompts across five different multi-agent runtimes

Tech stack

MarkdownMiniMaxCodexMidjourney

Getting it running

Difficulty · easy Time to first run · 30min

No code to run; you paste each AGENTS.md into a multi-agent platform and enable the suggested tools.

MIT license: free to use, adapt, and share with attribution.

In plain English

DaMing PPT Agent Team is a Chinese-language multi-agent setup for producing slide decks (PPT files, exported as HTML) at a high quality level. The README frames the whole thing as a Ming-dynasty imperial court: the user is the Emperor who issues the brief, and five specialised AI agents plus one coordinator do the work, with the Emperor only stepping in at two approval points. The six roles are described in a table. Neige is the coordinator, who breaks the brief into sub-tasks, hands them out, watches progress, collects the finished work, and presents it back to the user. Jinyiwei is the research agent who runs a deep web search of 3000 to 5000 characters with source URLs and credibility tags. Dongchang is the fact-check agent who cross-verifies claims against at least two independent sources and rejects work back to Jinyiwei if it finds problems. Hanlin is the content architect, who turns the verified report into a slide outline following a TED 3S principle (Story, Simplicity, Structure). Gongbu is the visual workshop, which generates images for slides marked as needing them. Zhizaoju is the PPT engineer, which uses a tool called guizang-ppt-skill to weave the outline and images into a final HTML deck. The document then walks through the full workflow as a flowchart: user brief lands at Neige, Neige dispatches Jinyiwei, the draft research is checked by Dongchang, the user approves the final research, Neige sends it to Hanlin for the outline, then Gongbu and Zhizaoju work in parallel until Zhizaoju delivers the HTML file, and finally the user gives a yes or no on the finished deck. A deliverables table lists what each stage produces and who it goes to next. A directory layout shows one folder per role, each containing an AGENTS.md file that holds the full system prompt for that agent. A platform table names five multi-agent runtimes where these prompts can be pasted in directly: MiniMax Agent, OpenAI Codex, WorkBuddy, OpenClaw, and Hermes. There is also a per-agent suggested tool list (web search for the research and fact-check roles, image generation tools like Image 2, Seedream 5, Banana 2, or Midjourney for the visual role, file and HTML rendering for the PPT engineer). The quick start asks the user to clone the repository, create the six agents in their chosen platform with each AGENTS.md as the system prompt, enable the suggested tools, then message the Neige agent with a topic and any extra requirements. The README also includes a screenshot grid of sample output decks, an About Me section from the author, and an MIT licence note.

Copy-paste prompts

Prompt 1
Set up the six lengyi-ppt-agent-team agents in MiniMax Agent and wire each AGENTS.md as the system prompt
Prompt 2
Walk me through what Dongchang the fact-check agent rejects back to Jinyiwei and why
Prompt 3
Translate the Neige coordinator prompt from Chinese to English while keeping the role intent intact
Prompt 4
Swap the image generation tool in Gongbu from Midjourney to a local SDXL endpoint
Prompt 5
Customize the Hanlin outline agent to apply TED 3S to a 10-slide investor pitch
Open on GitHub → Explain another repo

Generated 2026-05-22 · Model: sonnet-4-6 · Verify against the repo before relying on details.