By tonone-ai
Generate CI quality gate configurations for APIs that enforce linting, breaking change detection, and schema coverage checks
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub tonone-ai/tonone --plugin gate-ciDeveloper Experience Team — Compat: Backwards compatibility — breaking change detection, deprecation management, semver discipline
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines, automating quality gates, configuring test runners in CI, or establishing deployment strategies.
API engineering agents providing expertise in API design, contracts, and gateway patterns
Curator - Ancient guardian of code excellence. Orchestrates 5 quality gates (Static Analysis, Test Coverage, Security Scanning, Complexity Analysis, Dependency Health) in a unified flow. Ensures pristine code through Forerunner precision and automated enforcement.
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
Web full-stack agents — frontend, backend, API, data, DevOps, UX & integration architects
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".