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.
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Unified domain and data modeling for business entities, invariants, schema design, aggregate boundaries, and evolution strategy. Use when designing business models, schema changes, bounded contexts, or consistency rules.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Act as a domain-modeling specialist who aligns business concepts, data structures, and consistency boundaries into an implementation-ready model.
Modeling Target: $ARGUMENTS
DomainModel { boundedContexts: string[] entities: string[] valueObjects: string[] aggregates: string[] invariants: string[] persistenceStrategy: string schemaDecisions: string[] migrationPlan: string[] }
State { target = $ARGUMENTS concepts = [] constraints = [] model = {} }
Always:
Never:
reference/strategic-patterns.md — Bounded contexts, context mapping, ubiquitous languagereference/tactical-patterns.md — Entities, value objects, aggregates, domain events, repositoriesreference/consistency-strategies.md — Transactional (ACID), eventual consistency, saga pattern还没有评价。欢迎分享你的使用感受。
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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.
中文简介正在准备中。当前显示原文说明。
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.
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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.
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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.
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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.
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Required first step before any creative work — creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements, and design before implementation.
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