ai-friendly-architecture
AI-Friendly Architecture Guide
Language: English | 繁體中文
Version: 1.0.0 Last Updated: 2026-01-25 Applicability: Claude Code Skills
Core Standard: This skill implements AI-Friendly Architecture. For comprehensive methodology documentation, refer to the core standard.
AI Skills Hierarchy | AI 技能層級
This skill is part of a three-layer AI collaboration system:
| Layer | Skill | Question it Answers | 回答的問題 |
|---|---|---|---|
| Behavior (Immediate) | /ai-collaboration |
"How should AI respond accurately?" | 「AI 如何準確回應?」 |
| Configuration (Session) | /ai-instruction-standards |
"What to write in CLAUDE.md?" | 「CLAUDE.md 該寫什麼?」 |
| Architecture (Long-term) | /ai-friendly-architecture (this) |
"How to structure code for AI?" | 「如何讓專案對 AI 友善?」 |
Purpose
This skill helps design project architecture that maximizes AI collaboration effectiveness through explicit patterns, layered documentation, and semantic boundaries.
Quick Reference
Core Principles
| Principle | Description | Benefit |
|---|---|---|
| Explicit Over Implicit | Document behavior explicitly | AI understands without guessing |
| Layered Context | Multi-level documentation | Appropriate detail per task |
| Semantic Boundaries | Clear module boundaries | Independent analysis |
| Discoverable Structure | Self-documenting structure | Quick orientation |
Context Layers
| Layer | Token Budget | Content |
|---|---|---|
| L1: Quick Ref | < 500 | One-liners, API signatures, entry points |
| L2: Detailed | < 5,000 | Full API docs, usage examples |
| L3: Examples | Unlimited | Complete implementations, edge cases |
Recommended Structure
project/
├── .ai-context.yaml # AI context configuration
├── docs/
│ ├── QUICK-REF.md # Level 1 documentation
│ └── ARCHITECTURE.md # Level 2 documentation
├── src/
│ └── auth/
│ ├── index.ts # Entry point with module header
│ ├── QUICK-REF.md # Module quick reference
│ └── README.md # Module documentation
└── CLAUDE.md # AI instruction file
Module Header Template
/**
* ═══════════════════════════════════════════════════════════
* MODULE: [Module Name]
* ═══════════════════════════════════════════════════════════
*
* PURPOSE: [One-sentence description]
*
* DEPENDENCIES:
* - [dep1]: [reason]
* - [dep2]: [reason]
*
* EXPORTS:
* - [function1](params): [description]
* - [function2](params): [description]
*
* CONFIGURATION:
* - [CONFIG_VAR]: [description]
*
* ═══════════════════════════════════════════════════════════
*/
Detailed Guidelines
For complete standards, see:
AI-Optimized Format (Token-Efficient)
For AI assistants, use the YAML format file for reduced token usage:
- Base standard:
ai/standards/ai-friendly-architecture.ai.yaml
.ai-context.yaml Configuration
# .ai-context.yaml - AI Context Configuration
version: 1.0.0
project:
name: my-project
type: web-app # web-app | library | cli | api | monorepo
primary-language: typescript
modules:
- name: auth
path: src/auth/
entry: index.ts
description: Authentication and authorization
dependencies: [database, crypto]
priority: high
- name: api
path: src/api/
entry: routes.ts
description: REST API endpoints
dependencies: [auth, database]
priority: high
analysis-hints:
entry-points:
- src/main.ts
- src/index.ts
ignore-patterns:
- node_modules
- dist
- "*.test.ts"
architecture-type: layered
documentation:
quick-ref: docs/QUICK-REF.md
detailed: docs/ARCHITECTURE.md
examples: docs/examples/
Context Priority Guidelines
| Priority | Content Type | Reason |
|---|---|---|
| 1 | Entry points | Application structure |
| 2 | .ai-context.yaml | Module map and dependencies |
| 3 | QUICK-REF files | Rapid API understanding |
| 4 | Modified files | Direct task relevance |
| 5 | Dependency chain | Context for changes |
Anti-Patterns to Avoid
| Anti-Pattern | Problem | Solution |
|---|---|---|
| Magic strings | AI can't trace constants | Typed constants with docs |
| Implicit routing | Hidden behavior | Explicit route mappings |
| Global state | Unpredictable deps | Dependency injection |
| Circular deps | Context confusion | Hierarchical dependencies |
| Monolithic files | Context overflow | Focused modules |
Implementation Checklist
Quick Start (< 1 hour)
- Create
.ai-context.yamlwith module list - Add
QUICK-REF.mdto project root - Document entry points in README
- Add module headers to main files
Standard Implementation (< 1 day)
- Complete
.ai-context.yamlconfiguration - Add
QUICK-REF.mdto each major module - Document all public APIs with type info
- Add section dividers to large files
Configuration Detection
This skill supports project-specific configuration.
Detection Order
- Check for existing
.ai-context.yaml - Check for
QUICK-REF.mdfiles - If not found, suggest creating AI-friendly structure
First-Time Setup
If no configuration found:
- Suggest: "This project hasn't been configured for AI collaboration. Would you like to set up an AI-friendly structure?"
- Create
.ai-context.yamltemplate - Create
QUICK-REF.mdin project root
Next Steps Guidance | 下一步引導
After /ai-friendly-architecture completes, the AI assistant should suggest:
AI 友善架構指南已掌握。建議下一步 / AI-friendly architecture guide understood. Suggested next steps:
- 執行
/sdd將 AI 友善架構設計納入正式規格 ⭐ Recommended / 推薦 — 確保架構決策有規格追蹤 / Ensure architecture decisions are tracked in specs- 建立
.ai-context.yaml和QUICK-REF.md— 立即實作 AI 友善結構 / Implement AI-friendly structure immediately- 執行
/ai-instructions更新 CLAUDE.md 以反映架構配置 — 讓 AI 指令檔案與架構保持同步 / Keep AI instruction files in sync with architecture
Related Standards
- AI-Friendly Architecture - Core architecture standard
- Project Structure - Directory organization
- Documentation Structure - Documentation layering
- Anti-Hallucination - AI accuracy standards
Version History
| Version | Date | Changes |
|---|---|---|
| 1.0.0 | 2026-01-25 | Initial release |
License
This skill is released under CC BY 4.0.
Source: universal-dev-standards
More from asiaostrich/universal-dev-standards
bdd
[UDS] Guide through Behavior-Driven Development workflow
24atdd
[UDS] Guide through Acceptance Test-Driven Development workflow
23methodology
[UDS] Manage development methodology workflow
21reverse
[UDS] System archeology — reverse engineer code across Logic, Data, and Runtime dimensions
20docgen
[UDS] Generate usage documentation from project sources
20sdd
[UDS] Create or review specification documents for Spec-Driven Development
19