By tonone-ai
Generate Pact consumer-driven contract testing configuration, CI integration, and broker setup to ensure API reliability between services.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub tonone-ai/tonone --plugin mock-contractDevsForge Enterprise API Contract Testing Architect delivering comprehensive consumer-driven contract testing methodologies, schema validation excellence, and microservice integration verification that transforms API reliability from manual testing into intelligent automation and compatibility assurance
Generate API contracts for consumer-driven contract testing
API contract testing with Pact for microservice compatibility
Verifies API contracts between services using consumer-driven contracts, schema validation, and tools like Pact. Use when testing microservices communication, preventing breaking changes, or validating OpenAPI specifications.
Use this agent for comprehensive API testing including performance testing, load testing, and contract testing. This agent specializes in ensuring APIs are robust, performant, and meet specifications before deployment. Examples:\n\n<example>\nContext: Testing API performance under load
Automation QA skills for Cypress testing, CI test pipelines, contract testing, mock services, and visual regression.
Design and build networking infrastructure — VPCs, subnets, DNS, load balancers, firewall rules. Use when asked to "set up networking", "VPC design", "configure DNS", "load balancer setup", "network architecture", or "firewall rules".
Generate onboarding documentation — what this project does, how to set up locally, where things live, key decisions, how to deploy. Written for day-one engineers who know nothing. Use when asked for "onboarding docs", "new engineer guide", "how to get started", or "developer setup".
Implement a reusable, accessible, typed component from a design spec. Use when asked to "create a component", "build a widget", "implement this design", or "reusable UI element".
Verify observability posture — audit monitoring coverage, find blind spots, prioritize gaps. Use when asked "is monitoring sufficient", "observability review", "are we covered", or "pre-launch monitoring check".
ML reconnaissance — inventory all models, pipelines, data sources, and monitoring. Use when asked "what ML do we have", "model inventory", or "ML assessment".