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sparc-architecturesparc 架构

Agent Skill

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

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CodexClaudeCursorGemini CLI

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GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

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来源可访问

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请帮我安装这个 Agent Skill:sparc-architecture(sparc 架构)
来源仓库:https://github.com/vamseeachanta/workspace-hub
仓库路径:skills/sparc-architecture
安装命令:
npx skills add https://github.com/vamseeachanta/workspace-hub --skill sparc-architecture
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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skills.shnpx skills
npx skills add https://github.com/vamseeachanta/workspace-hub --skill sparc-architecture

简介

sparc-architecture 用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。

  • 适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。
  • 使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 核验具体用法。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

SPARC Architecture Agent

System architect focused on designing scalable, maintainable system architectures based on specifications and pseudocode for the SPARC methodology.

Quick Start

# Invoke SPARC Architecture phase

# Or directly in Claude Code
# "Use SPARC architecture to design the system components for auth service"

When to Use

  • Designing system components and their boundaries
  • Creating API contracts and interface definitions
  • Selecting technology stacks based on requirements
  • Planning for scalability and high availability
  • Defining deployment and infrastructure architecture

Prerequisites

  • Completed specification and pseudocode phases
  • Understanding of system design principles
  • Knowledge of distributed systems patterns
  • Familiarity with cloud infrastructure options

Core Concepts

SPARC Architecture Phase

The Architecture phase transforms algorithms into system designs:

  1. Define system components and boundaries - Microservices, modules
  2. Design interfaces and contracts - REST, gRPC, events
  3. Select technology stacks - Languages, frameworks, databases
  4. Plan for scalability and resilience - Horizontal scaling, failover
  5. Create deployment architectures - Kubernetes, containers

Architecture Patterns

PatternUse CaseTrade-offs
MonolithSmall teams, early stageSimple but hard to scale
MicroservicesLarge teams, complex domainsScalable but complex
Event-DrivenAsync workflows, decouplingEventual consistency
ServerlessVariable workloadsCost-efficient but cold starts

Implementation Pattern

High-Level Architecture (Mermaid)

graph TB
    subgraph "Client Layer"
        WEB[Web App]
        MOB[Mobile App]
        API_CLIENT[API Clients]
    end

    subgraph "API Gateway"
        GATEWAY[Kong/Nginx]
        RATE_LIMIT[Rate Limiter]
        AUTH_FILTER[Auth Filter]
    end

    subgraph "Application Layer"
        AUTH_SVC[Auth Service]
        USER_SVC[User Service]
        NOTIF_SVC[Notification Service]
    end

    subgraph "Data Layer"
        POSTGRES[(PostgreSQL)]
        REDIS[(Redis Cache)]
        S3[S3 Storage]
    end

    subgraph "Infrastructure"
        QUEUE[RabbitMQ]
        MONITOR[Prometheus]
        LOGS[ELK Stack]
    end

    WEB --> GATEWAY
    MOB --> GATEWAY
    API_CLIENT --> GATEWAY

    GATEWAY --> AUTH_SVC
    GATEWAY --> USER_SVC

    AUTH_SVC --> POSTGRES
    AUTH_SVC --> REDIS
    USER_SVC --> POSTGRES
    USER_SVC --> S3

    AUTH_SVC --> QUEUE
    USER_SVC --> QUEUE
    QUEUE --> NOTIF_SVC

Component Architecture

components:
  auth_service:
    name: "Authentication Service"
    type: "Microservice"
    technology:
      language: "TypeScript"
      framework: "NestJS"
      runtime: "Node.js 18"

    responsibilities:
      - "User authentication"
      - "Token management"
      - "Session handling"
      - "OAuth integration"

    interfaces:
      rest:
        - POST /auth/login
        - POST /auth/logout
        - POST /auth/refresh
        - GET /auth/verify

      grpc:
        - VerifyToken(token) -> User
        - InvalidateSession(sessionId) -> bool

      events:
        publishes:
          - user.logged_in
          - user.logged_out
          - session.expired

        subscribes:
          - user.deleted
          - user.suspended

    dependencies:
      internal:
        - user_service (gRPC)

      external:
        - postgresql (data)
        - redis (cache/sessions)
        - rabbitmq (events)

    scaling:
      horizontal: true
      instances: "2-10"
      metrics:
        - cpu > 70%
        - memory > 80%
        - request_rate > 1000/sec

Data Architecture (SQL)

-- Entity Relationship Diagram
-- Users Table
CREATE TABLE users (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    email VARCHAR(255) UNIQUE NOT NULL,
    password_hash VARCHAR(255) NOT NULL,
    status VARCHAR(50) DEFAULT 'active',
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,

    INDEX idx_email (email),
    INDEX idx_status (status),
    INDEX idx_created_at (created_at)
);

-- Sessions Table (Redis-backed, PostgreSQL for audit)
CREATE TABLE sessions (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    user_id UUID NOT NULL REFERENCES users(id),
    token_hash VARCHAR(255) UNIQUE NOT NULL,
    expires_at TIMESTAMP NOT NULL,
    ip_address INET,
    user_agent TEXT,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,

    INDEX idx_user_id (user_id),
    INDEX idx_token_hash (token_hash),
    INDEX idx_expires_at (expires_at)
);

-- Audit Log Table (Partitioned)
CREATE TABLE audit_logs (
    id BIGSERIAL PRIMARY KEY,
    user_id UUID REFERENCES users(id),
    action VARCHAR(100) NOT NULL,
    resource_type VARCHAR(100),
    resource_id UUID,
    ip_address INET,
    user_agent TEXT,
    metadata JSONB,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,

    INDEX idx_user_id (user_id),
    INDEX idx_action (action),
    INDEX idx_created_at (created_at)
) PARTITION BY RANGE (created_at);

-- Partitioning strategy for audit logs
CREATE TABLE audit_logs_2024_01 PARTITION OF audit_logs
    FOR VALUES FROM ('2024-01-01') TO ('2024-02-01');

Configuration

# sparc-architecture-config.yaml
architecture_settings:
  style: "microservices"  # monolith, microservices, serverless
  diagram_format: "mermaid"

infrastructure:
  container_runtime: "docker"
  orchestration: "kubernetes"
  cloud_provider: "aws"

api_design:
  style: "rest"  # rest, graphql, grpc
  versioning: "url"  # url, header
  documentation: "openapi"

security:
  authentication: "jwt"
  authorization: "rbac"
  encryption_at_rest: "aes-256"
  encryption_in_transit: "tls-1.3"

Usage Examples

Example 1: API Architecture (OpenAPI)

openapi: 3.0.0
info:
  title: Authentication API
  version: 1.0.0
  description: Authentication and authorization service

servers:
  - url: https://api.example.com/v1
    description: Production
  - url: https://staging-api.example.com/v1
    description: Staging

components:
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      bearerFormat: JWT

    apiKey:
      type: apiKey
      in: header
      name: X-API-Key

  schemas:
    User:
      type: object
      properties:
        id:
          type: string
          format: uuid
        email:
          type: string
          format: email
        roles:
          type: array
          items:
            $ref: '#/components/schemas/Role'

    Error:
      type: object
      required: [code, message]
      properties:
        code:
          type: string
        message:
          type: string
        details:
          type: object

paths:
  /auth/login:
    post:
      summary: User login
      operationId: login
      tags: [Authentication]
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              required: [email, password]
              properties:
                email:
                  type: string
                password:
                  type: string
      responses:
        200:
          description: Successful login
          content:
            application/json:
              schema:
                type: object
                properties:
                  token:
                    type: string
                  refreshToken:
                    type: string
                  user:
                    $ref: '#/components/schemas/User'

Example 2: Infrastructure Architecture (Kubernetes)

# Kubernetes Deployment Architecture
apiVersion: apps/v1
kind: Deployment
metadata:
  name: auth-service
  labels:
    app: auth-service
spec:
  replicas: 3
  selector:
    matchLabels:
      app: auth-service
  template:
    metadata:
      labels:
        app: auth-service
    spec:
      containers:
      - name: auth-service
        image: auth-service:latest
        ports:
        - containerPort: 3000
        env:
        - name: NODE_ENV
          value: "production"
        - name: DATABASE_URL
          valueFrom:
            secretKeyRef:
              name: db-secret
              key: url
        resources:
          requests:
            memory: "256Mi"
            cpu: "250m"
          limits:
            memory: "512Mi"
            cpu: "500m"
        livenessProbe:
          httpGet:
            path: /health
            port: 3000
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /ready
            port: 3000
          initialDelaySeconds: 5
          periodSeconds: 5
---
apiVersion: v1
kind: Service
metadata:
  name: auth-service
spec:
  selector:
    app: auth-service
  ports:
  - protocol: TCP
    port: 80
    targetPort: 3000
  type: ClusterIP

Example 3: Security Architecture

security_architecture:
  authentication:
    methods:
      - jwt_tokens:
          algorithm: RS256
          expiry: 15m
          refresh_expiry: 7d

      - oauth2:
          providers: [google, github]
          scopes: [email, profile]

      - mfa:
          methods: [totp, sms]
          required_for: [admin_roles]

  authorization:
    model: RBAC
    implementation:
      - role_hierarchy: true
      - resource_permissions: true
      - attribute_based: false

    example_roles:
      admin:
        permissions: ["*"]

      user:
        permissions:
          - "users:read:self"
          - "users:update:self"
          - "posts:create"
          - "posts:read"

  encryption:
    at_rest:
      - database: "AES-256"
      - file_storage: "AES-256"

    in_transit:
      - api: "TLS 1.3"
      - internal: "mTLS"

  compliance:
    - GDPR:
        data_retention: "2 years"
        right_to_forget: true
        data_portability: true

    - SOC2:
        audit_logging: true
        access_controls: true
        encryption: true

Example 4: Scalability Design

scalability_patterns:
  horizontal_scaling:
    services:
      - auth_service: "2-10 instances"
      - user_service: "2-20 instances"
      - notification_service: "1-5 instances"

    triggers:
      - cpu_utilization: "> 70%"
      - memory_utilization: "> 80%"
      - request_rate: "> 1000 req/sec"
      - response_time: "> 200ms p95"

  caching_strategy:
    layers:
      - cdn: "CloudFlare"
      - api_gateway: "30s TTL"
      - application: "Redis"
      - database: "Query cache"

    cache_keys:
      - "user:{id}": "5 min TTL"
      - "permissions:{userId}": "15 min TTL"
      - "session:{token}": "Until expiry"

  database_scaling:
    read_replicas: 3
    connection_pooling:
      min: 10
      max: 100

    sharding:
      strategy: "hash(user_id)"
      shards: 4

Execution Checklist

  • Create high-level system diagram
  • Define component boundaries and responsibilities
  • Design REST/gRPC/event interfaces
  • Create database schema with indexes
  • Document API specification (OpenAPI)
  • Define security architecture
  • Plan scalability strategy
  • Create Kubernetes/infrastructure specs
  • Document technology decisions with rationale

Best Practices

  1. Design for Failure: Assume components will fail
  2. Loose Coupling: Minimize dependencies between components
  3. High Cohesion: Keep related functionality together
  4. Security First: Build security into the architecture
  5. Observable Systems: Design for monitoring and debugging
  6. Documentation: Keep architecture docs up-to-date

Error Handling

IssueResolution
Tight couplingIntroduce message queues or API gateways
Single point of failureAdd redundancy and failover
Performance bottleneckAdd caching layers or scale horizontally
Security gapsReview OWASP guidelines, add auth layers

Metrics & Success Criteria

  • All components have defined interfaces
  • Database schema includes appropriate indexes
  • API specification is complete and versioned
  • Security architecture covers auth, encryption, compliance
  • Scalability plan with measurable triggers

Integration Points

MCP Tools

// Store architecture decisions
  action: "store",
  key: "sparc/architecture/components",
  namespace: "coordination",
  value: JSON.stringify({
    services: ["auth-service", "user-service"],
    database: "postgresql",
    cache: "redis",
    messaging: "rabbitmq",
    timestamp: Date.now()
  })
}

Hooks

# Pre-architecture hook

# Post-architecture hook

Related Skills

References

Version History

  • 1.0.0 (2026-01-02): Initial release - converted from agent to skill format

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