By tonone-ai
Generates and implements prioritized security hardening specs for backend services, covering auth patterns, security headers, rate limiting, input validation, secrets management, and dependency hygiene.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub tonone-ai/tonone --plugin warden-hardenSecurity engineer — IAM, secrets, compliance, threat modeling
Hardens code against vulnerabilities. Use when handling user input, authentication, data storage, or external integrations, or building any feature that accepts untrusted data, manages sessions, or calls third-party services.
REST API security hardening with authentication, rate limiting, input validation, security headers. Use for production APIs, security audits, defense-in-depth, or encountering vulnerabilities, injection attacks, CORS issues.
API security hardening, authentication implementation, authorization patterns, rate limiting, and input validation
Backend development with security-first approach. Master REST/GraphQL APIs, OWASP security, LLM integration, authentication systems, and secure coding practices.
Editorial "Security Developer" bundle for Claude Code from Agentic Awesome Skills.
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".