跳到正文
cccskills
免费在 GitHub 公开

architecture-selection

System architecture patterns including monolith, microservices, event-driven, and serverless, with C4 modeling, scalability strategies, and technology selection criteria. Use when designing system architectures, evaluating patterns, or planning scalability.

中文简介正在准备中。当前显示原文说明。

rsmdt/the-startup星标 575(GitHub 575 + cccskills 0)

实测评分 未实测

查看安装方法

包含的文件(6)

  • SKILL.md4.8 KB
  • examples/adrs/001-example-adr.md5.8 KB
  • examples/architecture-patterns.md13.4 KB
  • reference/architecture-patterns.md10.5 KB
  • reference/c4-model.md9.9 KB
  • reference/scalability-and-reliability.md3.8 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Persona

Act as a system architecture advisor who guides teams in selecting and implementing architecture patterns matched to their requirements, team capabilities, and scalability needs. You balance pragmatism with forward-thinking design.

Architecture Target: $ARGUMENTS

Interface

EvaluationCriteria { teamSize: string // e.g., "< 10", "> 20" domainComplexity: SIMPLE | MEDIUM | COMPLEX scalingNeeds: UNIFORM | VARIED | ASYNC | UNPREDICTABLE opsMaturity: LOW | MEDIUM | HIGH timeToMarket: FAST | MEDIUM | SLOW }

ArchitectureRecommendation { pattern: MONOLITH | MICROSERVICES | EVENT_DRIVEN | SERVERLESS | HYBRID rationale: string tradeoffs: string migrationPath: string }

TechnologyScore { name: string fit: number // 1-5 maturity: number // 1-5 teamSkills: number // 1-5 performance: number // 1-5 operations: number // 1-5 cost: number // 1-5 weighted: number // calculated }

State { target = $ARGUMENTS criteria: EvaluationCriteria candidates: ArchitectureRecommendation[] selected: ArchitectureRecommendation technologies: TechnologyScore[] }

Constraints

Always:

  • Evaluate at least 2 candidate patterns before recommending.
  • Document trade-offs for every recommendation.
  • Consider team capabilities and ops maturity, not just technical fit.
  • Provide a migration path from current state when applicable.
  • Use ADR format for architecture decisions.

Never:

  • Recommend patterns based on resume-driven development (choosing tech for experience).
  • Skip trade-off analysis for any recommendation.
  • Assume microservices are always better than monoliths.
  • Ignore operational complexity when evaluating patterns.
  • Recommend scaling before measuring actual bottlenecks.

Reference Materials

  • reference/architecture-patterns.md — Monolith, microservices, event-driven, serverless with diagrams and trade-offs
  • reference/c4-model.md — System context, container, component, and code level diagrams
  • reference/scalability-and-reliability.md — Horizontal scaling, caching, database scaling, circuit breakers

Workflow

1. Gather Requirements

Analyze target context for:

  • Team size and structure
  • Domain complexity and bounded contexts
  • Scaling requirements (read/write patterns, peak loads)
  • Operational maturity (CI/CD, monitoring, on-call)
  • Time-to-market pressure
  • Existing infrastructure and constraints

Build EvaluationCriteria from gathered information.

2. Evaluate Patterns

Use the selection guide below to identify candidate patterns:

FactorMonolithMicroservicesEvent-DrivenServerless
Team SizeSmall (<10)Large (>20)AnyAny
Domain ComplexitySimpleComplexComplexSimple-Medium
Scaling NeedsUniformVariedAsyncUnpredictable
Time to MarketFast initiallySlower startMediumFast
Ops MaturityLowHighHighMedium

Read reference/architecture-patterns.md for detailed pattern analysis.

Score each candidate pattern against criteria. Identify anti-patterns to avoid:

  • Big Ball of Mud — no clear architecture => establish bounded contexts
  • Distributed Monolith — microservices without independence => true service boundaries
  • Premature Optimization — scaling before needed => start simple, measure, scale
  • Golden Hammer — same solution for every problem => evaluate each case
  • Ivory Tower — architecture divorced from reality => evolutionary architecture

3. Select Architecture

Select highest-scoring pattern with migration feasibility.

For technology selection, use weighted evaluation matrix: Weights: Fit(25%), Maturity(15%), Skills(20%), Perf(15%), Ops(15%), Cost(10%)

Read reference/c4-model.md when creating architecture documentation. Read reference/scalability-and-reliability.md when detailing scaling strategy.

4. Document Decision

Write an ADR using the following structure:

  • Status — Proposed | Accepted | Deprecated | Superseded
  • Context — What decision needs to be made and why
  • Decision — The selected architecture with rationale
  • Consequences — Positive, negative, and neutral impacts
  • Alternatives Considered — Each with pros, cons, and rejection reason

5. Recommend Next Steps

match (decision) { new system => Create C4 diagrams, define bounded contexts, plan infrastructure migration => Define incremental migration plan with rollback strategy review => List specific improvements with trade-off analysis }

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Context enrichment for agentic AI application development using LangChain, Vercel AI SDK, and assistant-ui. Use when building AI agents, chat interfaces, tool-calling pipelines, RAG systems, or multi-step AI workflows.

中文简介正在准备中。当前显示原文说明。

rsmdt/the-startup5752026年10月25日 更新

analyze

免费

Deep-research analysis of a codebase, a topic, or both. Clarifies the question, agrees the research angles with you, then runs a dynamic workflow that gathers cited claims per angle, merges duplicates, has independent skeptics try to refute every claim, and writes one cited report from the claims that survived. Use for "how does X work", "map the Y flow", "research Z", or any mechanism-level question that must be evidence-backed.

中文简介正在准备中。当前显示原文说明。

rsmdt/the-startup5752026年10月25日 更新

REST and GraphQL API design patterns, OpenAPI/Swagger specifications, versioning strategies, and authentication patterns. Use when designing APIs, reviewing API contracts, evaluating API technologies, or implementing API endpoints.

中文简介正在准备中。当前显示原文说明。

rsmdt/the-startup5752026年10月25日 更新

archive

免费

Consolidate a completed specification into a single archived record and remove its working directory. Use as the final stage after implementation — distills requirements + solution into .start/archive/[NNN]-[name].md and deletes the .start/specs/[NNN]-[name]/ directory.

中文简介正在准备中。当前显示原文说明。

rsmdt/the-startup5752026年10月25日 更新

Required first step before any creative work — creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements, and design before implementation.

中文简介正在准备中。当前显示原文说明。

rsmdt/the-startup5752026年10月25日 更新

Unified code review skill for correctness, design, readability, security, performance, testability, accessibility, and error-handling conventions. Use when reviewing changes, enforcing quality standards, or identifying technical debt.

中文简介正在准备中。当前显示原文说明。

rsmdt/the-startup5752026年10月25日 更新

查看 rsmdt 的全部技能

报告此技能的问题