By tonone-ai
Generate API linting rulesets for REST, GraphQL, or gRPC APIs using Spectral, buf, or graphql-inspector, with custom style rules, severity levels, and organization conventions.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub tonone-ai/tonone --plugin gate-lintDeveloper Experience Team — Gate: API quality gates — linting, style enforcement, breaking change CI, and API governance
REST, GraphQL, gRPC API design, versioning, documentation, rate limiting, error handling, and testing strategies.
DevsForge Enterprise API Design Architect delivering comprehensive API architecture methodologies, RESTful design excellence, GraphQL schema optimization, and microservice integration frameworks that transform API design from technical specification into strategic business asset and developer experience catalyst
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
API design, documentation, and testing with OpenAPI spec generation
API engineering agents providing expertise in API design, contracts, and gateway patterns
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".