Best use case
backend-ai-guide is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
|
Teams using backend-ai-guide should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/backend-ai-guide/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How backend-ai-guide Compares
| Feature / Agent | backend-ai-guide | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
|
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Backend.AI Guide Skill ## Purpose This skill provides expert-level information about the Backend.AI platform by: - Fetching official documentation from the Backend.AI GitHub repository - Recursively exploring Major Components documentation links - Following relevant links to gather comprehensive technical details - Providing accurate, source-backed answers about Backend.AI architecture and features ## When to Use Activate this skill when the user asks about: - Backend.AI platform overview or architecture - Backend.AI components (Manager, Agent, Storage Proxy, Webserver, App Proxy) - Backend.AI setup, requirements, or infrastructure - Backend.AI APIs (REST, GraphQL) - Backend.AI features (session scheduling, resource allocation, multi-tenancy) - Backend.AI kernels, containers, or runtime elements - How the WebUI connects to or interacts with Backend.AI backend - Differences between Backend.AI components ## Primary Documentation Sources 1. **Main README**: https://github.com/lablup/backend.ai/blob/main/README.md - Overview and architecture - Major Components section with component links - Requirements and setup information 2. **Major Component READMEs**: Follow links from the Major Components section - Manager component details - Agent component details - Storage Proxy details - Webserver details - App Proxy details - And other components 3. **Recursive Link Following**: When a component README references additional documentation, follow those links to gather comprehensive information ## Instructions ### Step 1: Identify the Question Scope - Determine what aspect of Backend.AI the user is asking about - Identify which components or features are relevant ### Step 2: Fetch the Main README - Always start by fetching: https://github.com/lablup/backend.ai/blob/main/README.md - Extract key information relevant to the question - Identify links to Major Components that need to be explored ### Step 3: Recursively Fetch Component Documentation - For questions about specific components, fetch their individual READMEs - Component README links are found in the "Major Components" section - Example component paths (adjust based on actual links): - Manager: `src/ai/backend/manager/README.md` - Agent: `src/ai/backend/agent/README.md` - Storage Proxy: `src/ai/backend/storage/README.md` - Webserver: `src/ai/backend/web/README.md` - App Proxy: `src/ai/backend/appproxy/README.md` ### Step 4: Follow Additional Links - If component READMEs reference additional documentation, follow those links - Common additional documentation types: - Architecture diagrams - API documentation - Configuration guides - Development guides - **Important**: Only follow links that are relevant to answering the user's question ### Step 5: Synthesize and Present Information - Combine information from all fetched sources - Structure the answer logically: 1. Direct answer to the user's question 2. Supporting details from official documentation 3. Related component interactions (if applicable) 4. Links to source documentation for further reading - Use clear headings and formatting - Include code examples or configuration snippets when relevant ## Best Practices 1. **Always Cite Sources** - Reference the specific documentation URLs you fetched - Help users find more detailed information 2. **Stay Current** - Fetch documentation fresh each time (don't rely on cached knowledge) - Note version requirements (Python, Docker, PostgreSQL, etc.) 3. **Explain Component Interactions** - Backend.AI is a distributed system - explain how components work together - Clarify the relationship between WebUI (this project) and Backend.AI backend 4. **Be Precise with Technical Details** - Include version numbers, requirements, and configuration details - Distinguish between different API types (REST vs GraphQL) 5. **Limit Recursion Depth** - Fetch main README + relevant component READMEs - Only follow 1-2 additional link levels unless user needs deep details - Balance thoroughness with response time ## Example Question Types **Architecture Questions** - "How does Backend.AI work?" - "What is the architecture of Backend.AI?" - "What are the main components of Backend.AI?" **Component Questions** - "What does the Backend.AI Manager do?" - "How does the Agent component work?" - "What is the Storage Proxy?" **Integration Questions** - "How does this WebUI connect to Backend.AI?" - "What APIs does Backend.AI expose?" - "How do I authenticate with Backend.AI?" **Setup Questions** - "What are the requirements for Backend.AI?" - "How do I set up Backend.AI?" - "What infrastructure does Backend.AI need?" ## Response Format Structure answers as follows: ```markdown ## [Direct Answer to Question] [Concise, direct answer based on official documentation] ## Details [Supporting information from fetched documentation] ### Component Interactions (if applicable) [How different components work together] ## Technical Specifications (if applicable) - Requirements: [versions, dependencies] - Configuration: [relevant settings] - APIs: [REST/GraphQL endpoints] ## Source Documentation - Main: [URL to main README] - Component: [URLs to component READMEs] - Additional: [URLs to other relevant docs] ``` ## Notes - Backend.AI is the **backend platform** that this WebUI project connects to - This WebUI (backend.ai-webui) is a **client application** that uses Backend.AI's APIs - When users ask about "the backend" in this project context, they likely mean Backend.AI - Distinguish between WebUI code (this project) and Backend.AI platform code (separate repo) ## Limitations - This skill only fetches publicly available GitHub documentation - For questions requiring internal documentation or specific deployment details, direct users to Backend.AI team - Cannot access private repositories or non-public documentation
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