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senior-architect高级建筑师

Agent Skill

senior-architect 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

195,791

周安装

7,998

GitHub Stars

13

下载量

62,704
OpenClaw

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

MIT-0

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:senior-architect(高级建筑师)
来源仓库:https://github.com/alirezarezvani/senior-architect
安装命令:
openclaw skills install senior-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 OpenClaw 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。

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openclaw skills install senior-architect

简介

senior-architect 负责系统架构设计与技术选型评估。

  • 适用于复杂分布式系统或微服务改造项目的顶层设计。安装时按仓库提供的命令执行,建议先在测试环境验证依赖、命令权限和文件改动范围。
  • 输出架构图、非功能性需求矩阵和技术债务分析报告。
  • 重大架构变更需经过 POC 验证和团队共识才能落地。
  • 适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

SKILL.md

name
senior-architect
description
This skill should be used when the user asks to "design system architecture", "evaluate microservices vs monolith", "create architecture diagrams", "analyze dependencies", "choose a database", "plan for scalability", "make technical decisions", or "review system design". Use for architecture decision records (ADRs), tech stack evaluation, system design reviews, dependency analysis, and generating architecture diagrams in Mermaid, PlantUML, or ASCII format.

Senior Architect

Architecture design and analysis tools for making informed technical decisions.

Table of Contents

- Architecture Diagram Generator - Dependency Analyzer - Project Architect

- Database Selection - Architecture Pattern Selection - Monolith vs Microservices


Quick Start

# Generate architecture diagram from project
python scripts/architecture_diagram_generator.py ./my-project --format mermaid

# Analyze dependencies for issues
python scripts/dependency_analyzer.py ./my-project --output json

# Get architecture assessment
python scripts/project_architect.py ./my-project --verbose

Tools Overview

1. Architecture Diagram Generator

Generates architecture diagrams from project structure in multiple formats.

Solves: "I need to visualize my system architecture for documentation or team discussion"

Input: Project directory path Output: Diagram code (Mermaid, PlantUML, or ASCII)

Supported diagram types:

  • component - Shows modules and their relationships
  • layer - Shows architectural layers (presentation, business, data)
  • deployment - Shows deployment topology

Usage:

# Mermaid format (default)
python scripts/architecture_diagram_generator.py ./project --format mermaid --type component

# PlantUML format
python scripts/architecture_diagram_generator.py ./project --format plantuml --type layer

# ASCII format (terminal-friendly)
python scripts/architecture_diagram_generator.py ./project --format ascii

# Save to file
python scripts/architecture_diagram_generator.py ./project -o architecture.md

Example output (Mermaid):

graph TD
    A[API Gateway] --> B[Auth Service]
    A --> C[User Service]
    B --> D[(PostgreSQL)]
    C --> D

2. Dependency Analyzer

Analyzes project dependencies for coupling, circular dependencies, and outdated packages.

Solves: "I need to understand my dependency tree and identify potential issues"

Input: Project directory path Output: Analysis report (JSON or human-readable)

Analyzes:

  • Dependency tree (direct and transitive)
  • Circular dependencies between modules
  • Coupling score (0-100)
  • Outdated packages

Supported package managers:

  • npm/yarn (package.json)
  • Python (requirements.txt, pyproject.toml)
  • Go (go.mod)
  • Rust (Cargo.toml)

Usage:

# Human-readable report
python scripts/dependency_analyzer.py ./project

# JSON output for CI/CD integration
python scripts/dependency_analyzer.py ./project --output json

# Check only for circular dependencies
python scripts/dependency_analyzer.py ./project --check circular

# Verbose mode with recommendations
python scripts/dependency_analyzer.py ./project --verbose

Example output:

Dependency Analysis Report
==========================
Total dependencies: 47 (32 direct, 15 transitive)
Coupling score: 72/100 (moderate)

Issues found:
- CIRCULAR: auth → user → permissions → auth
- OUTDATED: lodash 4.17.15 → 4.17.21 (security)

Recommendations:
1. Extract shared interface to break circular dependency
2. Update lodash to fix CVE-2020-8203

3. Project Architect

Analyzes project structure and detects architectural patterns, code smells, and improvement opportunities.

Solves: "I want to understand the current architecture and identify areas for improvement"

Input: Project directory path Output: Architecture assessment report

Detects:

  • Architectural patterns (MVC, layered, hexagonal, microservices indicators)
  • Code organization issues (god classes, mixed concerns)
  • Layer violations
  • Missing architectural components

Usage:

# Full assessment
python scripts/project_architect.py ./project

# Verbose with detailed recommendations
python scripts/project_architect.py ./project --verbose

# JSON output
python scripts/project_architect.py ./project --output json

# Check specific aspect
python scripts/project_architect.py ./project --check layers

Example output:

Architecture Assessment
=======================
Detected pattern: Layered Architecture (confidence: 85%)

Structure analysis:
  ✓ controllers/  - Presentation layer detected
  ✓ services/     - Business logic layer detected
  ✓ repositories/ - Data access layer detected
  ⚠ models/       - Mixed domain and DTOs

Issues:
- LARGE FILE: UserService.ts (1,847 lines) - consider splitting
- MIXED CONCERNS: PaymentController contains business logic

Recommendations:
1. Split UserService into focused services
2. Move business logic from controllers to services
3. Separate domain models from DTOs

Decision Workflows

Database Selection Workflow

Use when choosing a database for a new project or migrating existing data.

Step 1: Identify data characteristics

CharacteristicPoints to SQLPoints to NoSQL
Structured with relationships
ACID transactions required
Flexible/evolving schema
Document-oriented data
Time-series data✓ (specialized)

Step 2: Evaluate scale requirements

  • <1M records, single region → PostgreSQL or MySQL
  • 1M-100M records, read-heavy → PostgreSQL with read replicas
  • >100M records, global distribution → CockroachDB, Spanner, or DynamoDB
  • High write throughput (>10K/sec) → Cassandra or ScyllaDB

Step 3: Check consistency requirements

  • Strong consistency required → SQL or CockroachDB
  • Eventual consistency acceptable → DynamoDB, Cassandra, MongoDB

Step 4: Document decision Create an ADR (Architecture Decision Record) with:

  • Context and requirements
  • Options considered
  • Decision and rationale
  • Trade-offs accepted

Quick reference:

PostgreSQL → Default choice for most applications
MongoDB    → Document store, flexible schema
Redis      → Caching, sessions, real-time features
DynamoDB   → Serverless, auto-scaling, AWS-native
TimescaleDB → Time-series data with SQL interface

Architecture Pattern Selection Workflow

Use when designing a new system or refactoring existing architecture.

Step 1: Assess team and project size

Team SizeRecommended Starting Point
1-3 developersModular monolith
4-10 developersModular monolith or service-oriented
10+ developersConsider microservices

Step 2: Evaluate deployment requirements

  • Single deployment unit acceptable → Monolith
  • Independent scaling needed → Microservices
  • Mixed (some services scale differently) → Hybrid

Step 3: Consider data boundaries

  • Shared database acceptable → Monolith or modular monolith
  • Strict data isolation required → Microservices with separate DBs
  • Event-driven communication fits → Event-sourcing/CQRS

Step 4: Match pattern to requirements

RequirementRecommended Pattern
Rapid MVP developmentModular Monolith
Independent team deploymentMicroservices
Complex domain logicDomain-Driven Design
High read/write ratio differenceCQRS
Audit trail requiredEvent Sourcing
Third-party integrationsHexagonal/Ports & Adapters

See references/architecture_patterns.md for detailed pattern descriptions.


Monolith vs Microservices Decision

Choose Monolith when:

  • [ ] Team is small (<10 developers)
  • [ ] Domain boundaries are unclear
  • [ ] Rapid iteration is priority
  • [ ] Operational complexity must be minimized
  • [ ] Shared database is acceptable

Choose Microservices when:

  • [ ] Teams can own services end-to-end
  • [ ] Independent deployment is critical
  • [ ] Different scaling requirements per component
  • [ ] Technology diversity is needed
  • [ ] Domain boundaries are well understood

Hybrid approach: Start with a modular monolith. Extract services only when:

  1. A module has significantly different scaling needs
  2. A team needs independent deployment
  3. Technology constraints require separation

Reference Documentation

Load these files for detailed information:

FileContainsLoad when user asks about
references/architecture_patterns.md9 architecture patterns with trade-offs, code examples, and when to use"which pattern?", "microservices vs monolith", "event-driven", "CQRS"
references/system_design_workflows.md6 step-by-step workflows for system design tasks"how to design?", "capacity planning", "API design", "migration"
references/tech_decision_guide.mdDecision matrices for technology choices"which database?", "which framework?", "which cloud?", "which cache?"

Tech Stack Coverage

Languages: TypeScript, JavaScript, Python, Go, Swift, Kotlin, Rust Frontend: React, Next.js, Vue, Angular, React Native, Flutter Backend: Node.js, Express, FastAPI, Go, GraphQL, REST Databases: PostgreSQL, MySQL, MongoDB, Redis, DynamoDB, Cassandra Infrastructure: Docker, Kubernetes, Terraform, AWS, GCP, Azure CI/CD: GitHub Actions, GitLab CI, CircleCI, Jenkins


Common Commands

# Architecture visualization
python scripts/architecture_diagram_generator.py . --format mermaid
python scripts/architecture_diagram_generator.py . --format plantuml
python scripts/architecture_diagram_generator.py . --format ascii

# Dependency analysis
python scripts/dependency_analyzer.py . --verbose
python scripts/dependency_analyzer.py . --check circular
python scripts/dependency_analyzer.py . --output json

# Architecture assessment
python scripts/project_architect.py . --verbose
python scripts/project_architect.py . --check layers
python scripts/project_architect.py . --output json

Getting Help

  1. Run any script with --help for usage information
  2. Check reference documentation for detailed patterns and workflows
  3. Use --verbose flag for detailed explanations and recommendations

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

82.07%
按下载量换算51,461

安全审计

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通过

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通过

权限和风险

可写文件

该 Skill 可能写入或修改本地文件,使用前需要确认目标目录和修改范围。

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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