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senior-architect高级建筑师

Agent Skill

senior-architect 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

759

周安装

31

GitHub Stars

1

下载量

246
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:senior-architect(高级建筑师)
来源仓库:https://github.com/pixel-process-ug/superkit-agents
仓库路径:skills/senior-architect
安装命令:
npx skills add https://github.com/pixel-process-ug/superkit-agents --skill 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 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/pixel-process-ug/superkit-agents --skill senior-architect

简介

senior-architect 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合围绕仓库状态和代码变更进行整理。

  • 适用于代码协作和仓库管理的信息处理,可结合协作事项使用。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限范围和维护状态。
  • 安装前建议确认是否会触发联网、命令执行或文件读写等操作边界。
  • 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

Senior Architect

Overview

Provide architecture-level guidance for system design decisions. This skill produces Architecture Decision Records (ADRs), trade-off analyses, scalability blueprints, and non-functional requirements specifications. Every recommendation includes explicit trade-offs and is grounded in proven patterns.

Announce at start: "I'm using the senior-architect skill for system design and architecture decisions."


Phase 1: Requirements Analysis

Goal: Capture all functional and non-functional requirements before designing.

Actions

  1. Identify functional requirements (capabilities)
  2. Define non-functional requirements (quality attributes)
  3. Identify constraints (budget, team, timeline, compliance)
  4. Map integration points with existing systems
  5. Establish success criteria and SLOs

STOP — Do NOT proceed to Phase 2 until:

  • Functional requirements are listed
  • Non-functional requirements are quantified (not vague)
  • Constraints are explicit
  • Success criteria are measurable

Phase 2: Architecture Design

Goal: Evaluate options and select the approach with the best trade-off profile.

Actions

  1. Evaluate architectural styles (monolith, microservices, event-driven)
  2. Design component boundaries and interfaces
  3. Define data architecture (storage, flow, consistency)
  4. Plan infrastructure and deployment topology
  5. Address cross-cutting concerns (auth, logging, monitoring)

Architecture Style Decision Table

FactorMonolithModular MonolithMicroservicesServerless
Team size < 10PreferredStrong fitOverkillGood for bursty
Team size > 30ChallengingGoodPreferredDepends
Domain well-understoodGood fitGood fitNot needed yetGood fit
Domain evolving rapidlyFine to startGood fitToo earlyGood fit
Need independent deploymentNot possibleLimitedKey benefitBuilt-in
Operational maturity lowGood fitGood fitHigh riskManaged risk
Variable/bursty loadOver-provisionedOver-provisionedPossibleStrong fit

Default Recommendation

Start with Modular Monolith: clear module boundaries, single deployment. Extract to microservices only when you have proven need for independent scaling, deployment, or team autonomy.

Trade-Off Analysis: Common Pairs

ImprovingMay Degrade
ConsistencyAvailability, Latency
PerformanceMaintainability, Cost
SecurityUsability, Performance
ScalabilitySimplicity, Cost
FlexibilityPerformance, Complexity
Time to MarketQuality, Scalability

Decision Matrix Template

Weight each quality attribute (1-5), score each option (1-5), multiply and sum.

| Quality Attribute  | Weight | Option A | Option B | Option C |
|--------------------|--------|----------|----------|----------|
| Performance        |   4    |  4 (16)  |  3 (12)  |  5 (20)  |
| Maintainability    |   5    |  5 (25)  |  4 (20)  |  2 (10)  |
| Scalability        |   3    |  3 (9)   |  5 (15)  |  4 (12)  |
| Cost               |   4    |  4 (16)  |  2 (8)   |  3 (12)  |
| Total              |        |    66    |    55    |    54    |

STOP — Do NOT proceed to Phase 3 until:

  • At least 2 architectural options have been evaluated
  • Trade-offs are explicitly documented
  • Decision matrix scores support the recommendation
  • Data architecture is defined

Phase 3: Documentation and Validation

Goal: Record decisions and validate against requirements.

Actions

  1. Write Architecture Decision Records for key decisions
  2. Create system context and container diagrams (C4 model)
  3. Validate against non-functional requirements
  4. Identify risks and mitigation strategies
  5. Define evolutionary architecture guardrails

ADR Format

# ADR-{number}: {Title}

## Status
Proposed | Accepted | Deprecated | Superseded by ADR-{number}

## Context
What is the issue motivating this decision?

## Decision
What change are we proposing?

## Consequences

### Positive
- [Benefit 1]
- [Benefit 2]

### Negative
- [Trade-off 1]
- [Trade-off 2]

### Risks
- [Risk and mitigation]

## Alternatives Considered
| Option | Pros | Cons | Verdict |
|--------|------|------|---------|
| Option A | ... | ... | Chosen |
| Option B | ... | ... | Rejected because... |

C4 Model Levels

LevelShowsWhen to Use
Level 1: System ContextUsers and external systemsAlways
Level 2: ContainerMajor technical building blocksAlways
Level 3: ComponentComponents within containersComplex services
Level 4: CodeClass-level detailCritical/complex areas only

STOP — Documentation complete when:

  • ADRs written for all key decisions
  • System context diagram created
  • NFRs validated against design
  • Risks documented with mitigations

Scalability Patterns

Horizontal Scaling Decision Table

PatternUse WhenImplementation
Load BalancingMultiple instances of same serviceRound-robin, least connections, IP hash
Stateless ServicesNeed to add/remove instances freelyJWT/external session store
Auto-scalingVariable load patternsCPU/memory/request-rate triggers
Read ReplicasRead-heavy workloadsRoute reads to replicas, writes to primary

Sharding Strategy Decision Table

StrategyHowGood For
Hash-basedConsistent hash of keyEven distribution
Range-basedDate range, ID rangeTime-series data
GeographicBy region/countryData locality
Tenant-basedPer customerMulti-tenant SaaS

Caching Layers

Client Cache (browser) -> CDN Cache -> API Gateway Cache ->
Application Cache (Redis) -> Database Query Cache -> Database

Non-Functional Requirements Template

## Performance
- Response time: p95 < 200ms, p99 < 500ms for API calls
- Throughput: 1000 RPS sustained, 5000 RPS peak
- Batch processing: 1M records/hour

## Availability
- Target: 99.9% (8.76h downtime/year)
- RTO (Recovery Time Objective): < 15 minutes
- RPO (Recovery Point Objective): < 5 minutes

## Scalability
- Current: 10K DAU
- 12-month target: 100K DAU
- Scale dimension: users, data volume, request rate

## Security
- Authentication: OAuth 2.0 / OIDC
- Authorization: RBAC with resource-level permissions
- Data encryption: at rest (AES-256) and in transit (TLS 1.3)

## Observability
- Logging: structured JSON, 30-day retention
- Metrics: RED method, custom business metrics
- Tracing: distributed tracing across all services
- Alerting: PagerDuty integration, tiered severity

SLO/SLA/SLI Framework

TermDefinitionExample
SLIMeasurable metricRequest latency, error rate
SLOTarget value99.9% availability
SLAContractual commitment99.5% with penalty clause
Error Budget1 - SLO0.1% = 8.76h/year

Anti-Patterns / Common Mistakes

Anti-PatternWhy It Is WrongCorrect Approach
Resume-driven architectureComplexity without benefitChoose simplest solution that works
Distributed monolithAll downsides of bothEither true monolith or true microservices
Premature optimizationScaling for 1M users with 100Design for current + 10x, not 1000x
Golden hammerOne technology for everythingRight tool for each problem
Architecture without validationUntested assumptionsLoad test, failure test, validate
Big upfront design without iterationRequirements changeEvolutionary architecture with guardrails
Vague NFRs ("fast", "scalable")Cannot be validatedQuantified targets with measurement

Subagent Dispatch Opportunities

Task PatternDispatch ToWhen
Analyzing different architecture layersAgent tool with subagent_type="Explore" (one per layer)When reviewing frontend, backend, and infra independently
Security assessment of architectureAgent tool invoking security-review skillWhen architecture involves auth, data flow, or external APIs
Performance implications analysisAgent tool invoking performance-optimization skillWhen architecture decisions affect latency or throughput
Code quality review of existing patternsAgent tool dispatching code-reviewer agentWhen evaluating current codebase for refactoring

Follow the dispatching-parallel-agents skill protocol when dispatching.


Integration Points

SkillRelationship
senior-backendBackend implementation follows architecture decisions
senior-fullstackFull-stack architecture follows service boundaries
security-reviewSecurity is a cross-cutting architectural concern
performance-optimizationPerformance NFRs drive optimization targets
planningArchitecture decisions inform implementation planning
code-reviewReview validates architectural consistency
acceptance-testingNFRs become acceptance criteria

Key Principles

  • Start with the simplest architecture that could work
  • Make decisions reversible when possible
  • Design for failure (everything will fail eventually)
  • Optimize for team cognitive load, not technical elegance
  • Document decisions, not just outcomes
  • Prefer boring technology for critical paths
  • Every architectural decision has a cost — make it explicit

Skill Type

FLEXIBLE — Adapt architecture recommendations to the specific context. ADRs are strongly recommended for all significant decisions. Trade-off analysis is mandatory. NFRs must be quantified, not described vaguely.

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

34.87%
按下载量换算86

Claude

31.39%
按下载量换算77

Cursor

20.15%
按下载量换算50

Gemini CLI

9.54%
按下载量换算23

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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