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system-architect系统架构师

Agent Skill

system-architect 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

490

周安装

20

GitHub Stars

20

下载量

158
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:system-architect(系统架构师)
来源仓库:https://github.com/georgekhananaev/claude-skills-vault
仓库路径:skills/system-architect
安装命令:
npx skills add https://github.com/georgekhananaev/claude-skills-vault --skill system-architect
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。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/georgekhananaev/claude-skills-vault --skill system-architect

简介

system-architect 用于查找、检索和筛选相关信息。

  • 适合根据关键词或任务场景快速定位候选结果。
  • 可通过 npx 命令从指定仓库安装使用。
  • 安装前应确认权限和维护状态,避免误触网络或文件操作。
  • 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

System Architect Skill

Design scalable, maintainable software systems.

When to Use

  • Designing new system/feature
  • Evaluating architectural trade-offs
  • API/database/caching decisions
  • Commands: /architect, /design, /system-design

Capabilities

1. System Design

  • Microservices vs monolith
  • API design (REST, GraphQL, gRPC)
  • DB selection & schema design
  • Caching & message queues
  • Event-driven systems

2. Scalability

  • Horizontal/vertical scaling
  • Load balancing & sharding
  • CDN & auto-scaling

3. Reliability

  • HA patterns & DR planning
  • Circuit breaker & retry
  • Graceful degradation

4. Security

  • Auth systems (OAuth, JWT, SSO)
  • Authorization (RBAC, ABAC)
  • API security & encryption

Architecture Decision Process

Step 1: Requirements

1. Functional: Core features, workflows, integrations
2. Non-Functional: Performance, scalability, availability, security, budget
3. Constraints: Tech stack, team expertise, timeline, existing systems

Step 2: Pattern Selection

Reference patterns.json for patterns, tech recommendations, trade-offs.

Step 3: Design Doc Template

# Architecture Design Document

## 1. Overview
[High-level description]

## 2. Goals & Non-Goals

## 3. Architecture
### System Diagram
### Components
| Component | Responsibility | Technology |
|-----------|---------------|------------|

### Data Flow

## 4. Technical Decisions
### Decision 1: [Title]
- Context | Options | Decision | Rationale

## 5. API Design
## 6. Data Model
## 7. Security
## 8. Scalability
## 9. Monitoring & Observability
## 10. Risks & Mitigations

Pattern Reference

Communication

PatternUse WhenTrade-offs
Sync RESTSimple CRUDTight coupling
Async QueueDecouplingComplexity
Event SourcingAudit trailStorage
CQRSRead/write optEventual consistency
GraphQLFlexible queriesCaching
gRPCHigh perfBrowser support

Data

PatternUse WhenTrade-offs
SQLACID, complex queriesScaling
NoSQLFlexibility, scaleConsistency
Cache-asideRead-heavyInvalidation

Resilience

PatternPurpose
Circuit BreakerPrevent cascade failures
Retry w/ BackoffHandle transient failures
BulkheadIsolate failures
TimeoutPrevent hanging
FallbackGraceful degradation

Project Structures

Reference structures.json for:

  • Python: FastAPI, Django
  • TypeScript: Next.js, React, Express
  • Java: Spring Boot
  • Go: Standard Layout

Tech Stack Recommendations

Web Apps

Frontend: React/Next.js, Vue/Nuxt, Angular
Backend: Node.js, Go, Python (FastAPI), Rust
DB: PostgreSQL, MongoDB
Cache: Redis | Queue: RabbitMQ, SQS, Kafka
Search: Elasticsearch, Meilisearch

Real-time

WebSocket: Socket.io, ws
Pub/Sub: Redis, Kafka

Data-Intensive

Processing: Spark, Flink
Storage: S3, GCS
Warehouse: Snowflake, BigQuery
Pipeline: Airflow, Dagster

Diagramming

ASCII Component

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│   Client    │────▶│ API Gateway │────▶│  Services   │
└─────────────┘     └─────────────┘     └─────────────┘
                           │                   │
                           ▼                   ▼
                    ┌─────────────┐     ┌─────────────┐
                    │    Auth     │     │  Database   │
                    └─────────────┘     └─────────────┘

Mermaid Sequence

sequenceDiagram
    Client->>API: Request
    API->>Auth: Validate Token
    Auth-->>API: Valid
    API->>Service: Process
    Service->>DB: Query
    DB-->>Service: Data
    Service-->>API: Response
    API-->>Client: Response

Evaluation Criteria

CriterionWeightDescription
ScalabilityHighCan it handle growth?
MaintainabilityHighEasy to modify/debug?
PerformanceMed-HighMeets latency/throughput?
CostMediumInfra + dev cost
SecurityHighMeets requirements?
ComplexityMediumTeam can build/operate?

Output Templates

Quick Decision

**Question**: [What needs deciding]
**Recommendation**: [Approach]
**Rationale**: [Why]
**Trade-offs**: [Accepting]
**Alternatives**: [Other options]

Integration

  • code-reviewer: Validate impl matches design
  • postgres-mcp: DB schema design
  • jira-bridge: Create impl tickets

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

32.43%
按下载量换算51

Claude

32.35%
按下载量换算51

Cursor

19.84%
按下载量换算31

Gemini CLI

9.33%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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