arcanea-architect

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Arcanea Architect Skill

Arcanea Architect Skill

Purpose

用途

This skill guides the design and implementation of the Arcanea ecosystem—the 64-agent creative intelligence system with multi-platform integration.
本Skill指导Arcanea生态系统的设计与实现——这是一个具备多平台集成能力的64-Agent创意智能系统。

When to Use

适用场景

  • Designing agent architectures
  • Implementing orchestration systems
  • Creating multi-platform integrations
  • Building creative AI tools
  • Establishing systematic workflows
  • 设计Agent架构
  • 实现编排系统
  • 创建多平台集成方案
  • 构建创意AI工具
  • 建立系统化工作流

Core Principles

核心原则

1. Excellence in Design

1. 卓越设计

  • Every component must have clear purpose
  • Architecture should be elegant, not clever
  • User experience is paramount
  • Code quality matters (tested, documented, maintainable)
  • 每个组件必须具备明确用途
  • 架构应简洁优雅,而非刻意炫技
  • 用户体验是重中之重
  • 重视代码质量(经过测试、文档完善、易于维护)

2. Attention to Detail

2. 注重细节

  • No shortcuts in critical paths
  • Validate all assumptions
  • Document reasoning for decisions
  • Test everything
  • 关键路径绝不走捷径
  • 验证所有假设
  • 记录决策的推理过程
  • 全面测试所有内容

3. Systematic Implementation

3. 系统化实施

  • Build foundation first, features second
  • Integration over isolation
  • Progressive enhancement
  • Backward compatibility when possible
  • 先搭建基础,再开发功能
  • 优先集成,避免孤立
  • 渐进式增强功能
  • 尽可能保持向后兼容性

Architecture Patterns

架构模式

Agent Registry Pattern

Agent注册模式

typescript
// Centralized agent definitions
interface Agent {
  id: string;           // Unique identifier
  name: string;         // Display name
  court: string;        // Elemental court
  frequency: string;    // Operating frequency
  specialty: string;    // What they do best
  skills: string[];     // Available skills
  prompts: Template[];  // Invocation templates
}
typescript
// Centralized agent definitions
interface Agent {
  id: string;           // Unique identifier
  name: string;         // Display name
  court: string;        // Elemental court
  frequency: string;    // Operating frequency
  specialty: string;    // What they do best
  skills: string[];     // Available skills
  prompts: Template[];  // Invocation templates
}

Conductor Pattern

指挥者模式

typescript
// Multi-agent orchestration
class Conductor {
  async orchestrate(task: Task): Promise<Result> {
    // 1. Analyze task complexity
    // 2. Select optimal agent team
    // 3. Determine execution strategy
    // 4. Execute with monitoring
    // 5. Learn from results
  }
}
typescript
// Multi-agent orchestration
class Conductor {
  async orchestrate(task: Task): Promise<Result> {
    // 1. Analyze task complexity
    // 2. Select optimal agent team
    // 3. Determine execution strategy
    // 4. Execute with monitoring
    // 5. Learn from results
  }
}

Skill Pattern

Skill模式

typescript
// Capability definitions
interface Skill {
  id: string;
  gate: number;         // Which gate (1-10)
  frequency: string;    // Associated frequency
  invocation: string;   // How to trigger
  process: Step[];      // Step-by-step procedure
  agents: string[];     // Which agents can use
}
typescript
// Capability definitions
interface Skill {
  id: string;
  gate: number;         // Which gate (1-10)
  frequency: string;    // Associated frequency
  invocation: string;   // How to trigger
  process: Step[];      // Step-by-step procedure
  agents: string[];     // Which agents can use
}

Implementation Checklist

实施检查清单

Phase 1: Foundation

第一阶段:基础搭建

  • Agent registry (64 agents defined)
  • Core conductor (orchestration engine)
  • Skill system (50+ skills)
  • AI router (opencode + Claude BYOK)
  • Documentation architecture
  • Agent注册中心(定义64个Agent)
  • 核心指挥者(编排引擎)
  • Skill系统(50+个Skill)
  • AI路由(opencode + Claude BYOK)
  • 文档架构

Phase 2: Integration

第二阶段:集成

  • .claude/CLAUDE.md (Claude Code)
  • .opencode/ skills (opencode editor)
  • Tauri desktop app
  • VS Code extension
  • Obsidian plugin
  • .claude/CLAUDE.md (Claude Code)
  • .opencode/ skills (opencode编辑器)
  • Tauri桌面应用
  • VS Code扩展
  • Obsidian插件

Phase 3: Polish

第三阶段:优化打磨

  • UI/UX refinement
  • Performance optimization
  • Error handling
  • User onboarding
  • Testing & validation
  • UI/UX优化
  • 性能调优
  • 错误处理
  • 用户引导
  • 测试与验证

Design Decisions

设计决策

Why 64 Agents?

为何选择64个Agent?

Decision: Use I Ching structure (8×8 = 64) Reasoning:
  • Complete symbolic system
  • Sacred geometry (8 = cosmic order)
  • Manageable yet comprehensive
  • Each can spawn sub-agents
决策: 采用《易经》结构(8×8=64) 理由:
  • 完整的符号系统
  • 神圣几何(8代表宇宙秩序)
  • 兼具可管理性与全面性
  • 每个Agent可衍生子Agent

Why Ten Gates?

为何设置十个Gate?

Decision: Solfeggio frequency scale (174-1111Hz) Reasoning:
  • Historical resonance
  • Metaphorical value
  • Organizational clarity
  • Memorable categorization
决策: 采用Solfeggio频率音阶(174-1111Hz) 理由:
  • 历史共鸣性
  • 隐喻价值
  • 组织清晰度
  • 易于记忆的分类方式

Why Hybrid AI?

为何采用混合AI方案?

Decision: opencode primary + Claude BYOK Reasoning:
  • Local-first (privacy, speed)
  • Cost efficiency (free tier for most tasks)
  • No vendor lock-in
  • User control
决策: 以opencode为主 + Claude BYOK 理由:
  • 本地优先(隐私性、速度)
  • 成本效益(多数任务可使用免费层级)
  • 无供应商锁定
  • 用户可控

Why Tauri Desktop?

为何选择Tauri桌面框架?

Decision: Tauri over Electron Reasoning:
  • Smaller bundle (600KB vs 100MB)
  • Rust performance
  • Native OS integration
  • Better security
决策: 选用Tauri而非Electron 理由:
  • 包体积更小(600KB vs 100MB)
  • Rust性能优势
  • 原生系统集成
  • 更高的安全性

Quality Standards

质量标准

Code Quality

代码质量

  • TypeScript strict mode
  • Comprehensive error handling
  • Unit tests for core logic
  • Integration tests for workflows
  • Documentation for all public APIs
  • TypeScript严格模式
  • 全面的错误处理
  • 核心逻辑单元测试
  • 工作流集成测试
  • 所有公开API均有文档

User Experience

用户体验

  • Sub-500ms response times
  • Clear error messages
  • Progressive disclosure
  • Offline capability
  • Consistent cross-platform UI
  • 响应时间低于500毫秒
  • 清晰的错误提示
  • 渐进式信息展示
  • 离线使用能力
  • 跨平台UI一致性

Performance

性能

  • LRU caching for AI responses
  • Lazy loading for agents
  • Debounced UI updates
  • Optimized renders
  • Memory management
  • AI响应结果的LRU缓存
  • Agent懒加载
  • UI更新防抖处理
  • 渲染优化
  • 内存管理

Resources

资源

Documentation

文档

  • AGENT_ARCHITECTURE_v4.md
    - Why 64 agents
  • IMPLEMENTATION_ARCHITECTURE.md
    - How it fits
  • BYOK_SAAS_ARCHITECTURE.md
    - AI integration
  • SKILL_ARCHITECTURE_ANALYSIS.md
    - Skills system
  • AGENT_ARCHITECTURE_v4.md
    - 为何采用64个Agent
  • IMPLEMENTATION_ARCHITECTURE.md
    - 系统适配方式
  • BYOK_SAAS_ARCHITECTURE.md
    - AI集成方案
  • SKILL_ARCHITECTURE_ANALYSIS.md
    - Skill系统分析

Code

代码

  • arcanea-agents/
    - Agent registry and conductor
  • desktop/
    - Tauri desktop application
  • .claude/
    - Claude Code integration
  • .opencode/
    - opencode editor integration
  • arcanea-agents/
    - Agent注册中心与指挥者
  • desktop/
    - Tauri桌面应用
  • .claude/
    - Claude Code集成
  • .opencode/
    - opencode编辑器集成

Templates

模板

  • Use
    SKILL.md
    template for new skills
  • Use agent template for new agents
  • Use component templates for UI
  • 新建Skill使用
    SKILL.md
    模板
  • 新建Agent使用Agent模板
  • UI组件使用组件模板

Anti-Patterns to Avoid

需避免的反模式

Don't: Create agents without clear purpose ✅ Do: Every agent solves specific problems
Don't: Use frequencies as acoustic prescriptions ✅ Do: Use as metaphorical categories
Don't: Build features before foundation ✅ Do: Foundation first, features second
Don't: Lock users into specific AI provider ✅ Do: Support multiple providers (BYOK)
Don't: Over-engineer simple solutions ✅ Do: Elegant simplicity
切勿: 创建无明确用途的Agent ✅ 应当: 每个Agent解决特定问题
切勿: 将频率作为声学指令 ✅ 应当: 将其用作隐喻分类
切勿: 在基础未完成前开发功能 ✅ 应当: 先搭建基础,再开发功能
切勿: 将用户锁定在特定AI供应商 ✅ 应当: 支持多供应商(BYOK)
切勿: 对简单解决方案过度设计 ✅ 应当: 追求简洁优雅

Success Metrics

成功指标

  • Technical: 100% test pass rate, <500ms response time
  • User: Can complete tasks without documentation
  • Adoption: Daily active users, retention rate
  • Satisfaction: User feedback, feature requests
  • 技术层面: 测试通过率100%,响应时间<500ms
  • 用户层面: 无需文档即可完成任务
  • 采用率: 日活跃用户数、留存率
  • 满意度: 用户反馈、功能需求

Conclusion

结论

Building Arcanea requires:
  1. Vision - Clear understanding of what we're building
  2. Discipline - Following architecture, not shortcuts
  3. Craft - Attention to every detail
  4. Iteration - Build, test, refine, repeat
The foundation determines the height. Build it well.

This skill should be used whenever implementing or extending the Arcanea ecosystem.
构建Arcanea需要:
  1. 愿景 - 清晰理解我们要构建的系统
  2. 纪律 - 遵循架构规范,不走捷径
  3. 匠心 - 注重每一个细节
  4. 迭代 - 构建、测试、优化、重复
基础决定高度,务必扎实搭建。

在实施或扩展Arcanea生态系统时,应使用本Skill。