AgentSkillsCN

backend-ai-guide

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SKILL.md
--- frontmatter
name: backend-ai-guide
description: |
  Expert guide for Backend.AI distributed computing platform. Automatically
  activates when users ask about:
  - Backend.AI architecture, components (Manager, Agent, Storage Proxy, Webserver, App Proxy)
  - Features (session scheduling, Sokovan orchestrator, multi-tenancy, resource allocation)
  - APIs (REST, GraphQL), authentication, RBAC authorization
  - Container runtime (kernels, jail sandbox, hook library, virtual folders)
  - Accelerator support (CUDA, ROCm, TPU, NPU, Graphcore IPU)
  - Client SDKs (Python, Java, JavaScript, PHP)
  - Setup, requirements (Python 3.13+, Docker, PostgreSQL, Redis, etcd)
  - How WebUI connects to/interacts with Backend.AI backend
  - Plugin interfaces, development setup, infrastructure
  Use when user mentions "Backend.AI", "backend.ai", "Sokovan", component names,
  or asks about the backend platform this WebUI connects to.
 allowed-tools: WebFetch, Read

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

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