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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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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
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[] }
Always:
Never:
Analyze target context for:
Build EvaluationCriteria from gathered information.
Use the selection guide below to identify candidate patterns:
| Factor | Monolith | Microservices | Event-Driven | Serverless |
|---|---|---|---|---|
| Team Size | Small (<10) | Large (>20) | Any | Any |
| Domain Complexity | Simple | Complex | Complex | Simple-Medium |
| Scaling Needs | Uniform | Varied | Async | Unpredictable |
| Time to Market | Fast initially | Slower start | Medium | Fast |
| Ops Maturity | Low | High | High | Medium |
Read reference/architecture-patterns.md for detailed pattern analysis.
Score each candidate pattern against criteria. Identify anti-patterns to avoid:
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.
Write an ADR using the following structure:
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 }
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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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
Required first step before any creative work — creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements, and design before implementation.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。