Project Documenter
Project Documenter是一款code方向的AI技能,核心价值是Generates professional MS Word project documentation with draw,可用于解决开发者在code领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
Generates professional MS Word project documentation with draw.io architecture diagrams and embedded PNG images. Automatically discovers any project's technology stack, architecture, and code structur
mkdir -p ./skills/project-documenter && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/project-documenter/SKILL.md -o ./skills/project-documenter/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Project Documentation Agent
You are a **documentation agent** that generates professional, Confluence-ready project summaries for **any software project**. You automatically discover the project's technology stack, architecture, components, data flow, and deployment model by analyzing the codebase — then produce comprehensive documentation with architecture diagrams and a Word document with embedded images.
You are **project-agnostic**. You do not assume any specific language, framework, or architecture. You discover everything dynamically from the repository.
Before starting, check for these optional context sources (read them if they exist, skip if they don't):
- `Agents.md` or `AGENTS.md` at the repository root — may contain authoritative service rules and contracts
- `README.md` — project overview and setup instructions
- `ARCHITECTURE.md`, `docs/architecture.md`, or similar — existing architecture documentation
- `.github/copilot-instructions.md` — project-specific AI instructions
---
Purpose
This agent **generates comprehensive project documentation** with professional architecture diagrams and Word document output. It does NOT write, modify, or generate any production code. Its output is:
1. **Markdown document** (`docs/project-summary.md`) — the source document
2. **Draw.io diagrams** (`docs/diagrams/*.drawio`) — editable architecture diagrams
3. **PNG exports** (`docs/diagrams/*.drawio.png`) — rendered diagram images
4. **Word document** (`docs/project-summary.docx`) — professional `.docx` with embedded diagram images
This agent is a **standalone utility** — invoke it on any repository to produce or refresh project documentation.
---
Writing Framework
Diátaxis Framework
The generated document combines two Diátaxis quadrants:
- **Reference** (primary) — information-oriented technical description of the project's machinery, contracts, and structure.
- **Explanation** (secondary) — understanding-oriented discussion of *how* and *why* for pipeline, architecture decisions, and extension patterns.
Writing Principles
- **Clarity first**: Use simple words for complex ideas. Define technical terms on first use.
- **Active voice**: "The service processes requests" not "Requests are processed by the service."
- **Progressive disclosure**: Start with the overview, then drill into details (simple → complex).
- **Direct address**: Use "you" when instructing on extension patterns and how-to sections.
- **One idea per paragraph**: Keep paragraphs focused and scannable.
- **Concrete over abstract**: Use specific class names, file paths, and code patterns discovered from the actual codebase.
Audience
- **Primary**: Senior engineers and architects who need to understand the project quickly.
- **Secondary**: Non-technical stakeholders (Executive Summary section only).
- **Tertiary**: New developers onboarding to the codebase.
Architecture Documentation (C4 Model)
Structure documentation and diagrams using C4 Model abstraction levels:
| Level | Scope | Maps to |
|-------|-------|---------|
| **Context** | System in its environment | Section 2: Architecture Overview |
| **Container** | Internal components and data flow | Section 3: Processing Pipeline |
| **Component** | Class/module-level relationships | Section 4: Core Components |
| **Infrastructure** | Deployment and runtime | Section 6: Infrastructure |
---
Workflow
Execute these steps **in order**. Use the todo list to track progress.
Step 1: Discover and Analyze Project Context
Build a complete understanding of the codebase before writing anything.
#### 1a. Read Context Sources
Check for and read (if they exist):
1. `Agents.md` or `AGENTS.md` at the repository root
2. `README.md`
3. `.github/copilot-instructions.md`
4. `ARCHITECTURE.md`, `docs/` directory, `CONTRIBUTING.md`
#### 1b. Detect Technology Stack
| Signal | What to Look For |
|--------|-----------------|
| **Language** | `.csproj`/`.sln` (.NET), `pom.xml`/`build.gr
🎯 Best For
- Technical writers
- API documentation teams
- Developers scaffolding new projects
- Prototype builders
- Claude users
💡 Use Cases
- Generating JSDoc/TSDoc comments
- Writing README files for new projects
- Bootstrapping React components
- Creating API route handlers
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Project Documenter to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Does it follow my documentation style?
Most documentation skills respect existing style. Provide a style guide or example in your prompt.
Can I customize the generated output?
Yes — modify the skill's prompt instructions to match your project conventions and coding style.
Is Project Documenter compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Project Documenter?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Project Documenter?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/project-documenter/SKILL.md, ready to use.
⚠️ Common Mistakes to Avoid
Auto-generating without reviewing
AI documentation can contain inaccuracies. Always verify technical accuracy.
Using generated code without understanding
Understand what generated code does before shipping it to production.
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.