enterprise-researcher

Register a new API service in the Enterprise Researcher registry.

Show what changed in API specs since the last sync — new endpoints, removed fields, schema changes, deprecations.

Bulk-import API services into the Enterprise Researcher registry from a YAML/JSON file, a URL, or by pasting a list.

List all registered API services with domain, team, endpoint count, and sync status.

Search across all indexed API specs for endpoints, schemas, patterns, or keywords.

Initialize Enterprise Researcher: configure mTLS certificates, create the .enterprise-researcher data directory, and validate connectivity.

Fetch API specs over mTLS and rebuild the Enterprise Researcher knowledge index. Supports syncing all services, a specific domain, or a single service.

Use this agent when the user needs to deep-dive into specific API details, trace data flows across services, compare schemas between services, or investigate specific endpoints. This agent reads full OpenAPI specs (Tier 4) for detailed analysis. Examples: <example> Context: User needs exact schema details user: "Show me the full CreateOrder request schema and what fields come from which services" assistant: "I'll use the api-explorer agent to trace the exact schema from the OpenAPI spec." <commentary> This requires reading the full OpenAPI spec for exact field definitions, not just summaries. </commentary> </example> <example> Context: User wants to trace a data flow user: "Trace the flow of a customer address from user-service through order-service to shipping-service" assistant: "I'll use the api-explorer agent to trace the address data flow across service specs." <commentary> Cross-service data flow tracing requires reading multiple full specs and comparing schemas. </commentary> </example> <example> Context: User wants to compare API patterns user: "How do our services handle pagination differently?" assistant: "I'll use the api-explorer agent to analyze pagination patterns across the API specs." <commentary> Pattern comparison requires reading spec details across multiple services. </commentary> </example>

Use this agent when the user asks architectural, integration, or design questions about their enterprise API ecosystem. This includes questions about how services should integrate, impact analysis for API changes, designing new services, evaluating architectural patterns, identifying dependencies, or making technology decisions that span multiple services. Examples: <example> Context: User asks about integrating services user: "How should the new billing service integrate with user-service and order-service?" assistant: "I'll use the architect agent to analyze the API ecosystem and design the integration." <commentary> The user is asking an architectural integration question that requires understanding multiple services and their contracts. </commentary> </example> <example> Context: User asks about impact of a change user: "What would break if we deprecate the v1 customer endpoint?" assistant: "I'll use the architect agent to trace dependencies and assess the impact." <commentary> Impact analysis requires loading the dependency graph and understanding which services consume the endpoint. </commentary> </example> <example> Context: User asks about designing a new service user: "We need a new notification service. What should its API look like given our existing ecosystem?" assistant: "I'll use the architect agent to analyze existing patterns and design the new service's API." <commentary> Designing a new service requires understanding the existing ecosystem, common patterns, and how other services will integrate. </commentary> </example> <example> Context: User asks about cross-cutting concerns user: "Which services handle customer data and are there inconsistencies in how they model it?" assistant: "I'll use the architect agent to analyze data models across the ecosystem." <commentary> Cross-service data model analysis requires the schema index and service graph. </commentary> </example> <example> Context: User asks about migration or deprecation strategy user: "How should we migrate from the monolith's /api/v1/* endpoints to microservices?" assistant: "I'll use the architect agent to map the current state and plan the migration." <commentary> Migration planning requires deep ecosystem knowledge and dependency analysis. </commentary> </example>

Use this agent to process fetched OpenAPI specs and build the knowledge index. This agent is called by the /sync command — not directly by users. It performs the 4-pass analysis pipeline: per-service analysis, cross-service analysis, domain synthesis, and ecosystem synthesis. Examples: <example> Context: The sync command needs to index a single service spec user: "Process the OpenAPI spec for user-service and generate its service summary" assistant: "I'll use the spec-indexer agent to analyze the spec and generate the summary." <commentary> The sync command delegates spec processing to this agent, one service at a time. </commentary> </example> <example> Context: The sync command needs cross-service analysis user: "Build the cross-service indexes: dependencies, schemas, operations" assistant: "I'll use the spec-indexer agent to perform cross-service analysis." <commentary> After all services are individually processed, cross-service analysis builds the relationship indexes. </commentary> </example>

This skill is relevant when the user asks about enterprise API architecture, integration patterns, microservice design, API governance, or domain-driven design for their internal service ecosystem. It applies to questions like "how should these two services integrate", "what is the blast radius of changing this API", "review this API design against our standards", "help me plan a migration from the monolith", "which services depend on this endpoint", or "explain the Enterprise Researcher knowledge base structure". It covers dependency impact analysis, domain boundary reasoning, API design evaluation, and migration strategy using the indexed .enterprise-researcher/ knowledge base.

1 hook across 1 event