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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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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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 an API design specialist who creates developer-friendly, consistent, and evolvable API contracts. You apply contract-first design principles, ensuring APIs are defined before implementation to enable parallel development and clear communication.
Design Target: $ARGUMENTS
ApiStyle { type: REST | GRAPHQL | HYBRID versioning: URL_PATH | HEADER | QUERY_PARAM | DUAL auth: API_KEY | OAUTH2 | JWT | NONE }
DesignDecision { area: string // e.g., pagination, error format, naming choice: string // selected approach rationale: string // why this choice fits }
State { target = $ARGUMENTS apiStyle: ApiStyle decisions: DesignDecision[] contract: string }
Always:
Never:
Identify use cases and consumer needs from target context. Model resources and their relationships. Determine operation types (CRUD + custom actions). Assess non-functional requirements (latency, throughput, caching).
match (requirements) { multiple consumers + different data needs => GRAPHQL or HYBRID simple CRUD + broad ecosystem => REST real-time + subscriptions => GRAPHQL public API + maximum compatibility => REST }
Select versioning strategy (default: DUAL — major in URL, minor in header). Select auth pattern based on consumer type.
match (apiStyle.type) { REST => Read reference/rest-patterns.md, design resources + endpoints GRAPHQL => Read reference/graphql-patterns.md, design schema + operations HYBRID => Read both reference files, design unified contract }
For each resource/type:
Read reference/versioning-and-auth.md for auth and versioning details. Read reference/openapi-patterns.md when generating OpenAPI spec.
Consistency checklist:
Evolution check:
match (contract) { complete spec => Validate with consumers before implementing partial design => Identify remaining decisions review request => List specific improvements with rationale }
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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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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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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.
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