By tonone-ai
Audits frontend projects for bundle size, dependency health, accessibility, performance, and component quality by analyzing build outputs and package.json.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub tonone-ai/tonone --plugin prism-auditFrontend reconnaissance — map the component tree, routing, state management, build config, and assess quality. Use when asked to "understand this frontend", "frontend assessment", or "what's the UI built with".
Frontend bundle size analysis and tree-shaking optimization
24 parallel audit agents + 6 workflow skills for Claude Code. Complete E2E development workflow for solo devs.
AI-powered performance optimization - Interactive performance audit skill and automated agent with comprehensive bottleneck detection and optimization
Comprehensive frontend development toolkit combining React, accessibility, performance, and responsive design. Includes frontend lead agent for holistic frontend decisions.
Use this agent for comprehensive performance testing, profiling, and optimization recommendations. This agent specializes in measuring speed, identifying bottlenecks, and providing actionable optimization strategies for applications. Examples:\n\n<example>\nContext: Application speed testing
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".