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Found 9 Skills
Analyze Rspack/Webpack bundles from local Rsdoctor build data without MCP. Zero-dependency JS CLI for chunk/module/package/loader insights.
Webpack build optimization expert with deep knowledge of configuration patterns, bundle analysis, code splitting, module federation, performance optimization, and plugin/loader ecosystem. Use PROACTIVELY for any Webpack bundling issues including complex optimizations, build performance, custom plugins/loaders, and modern architecture patterns. If a specialized expert is a better fit, I will recommend switching and stop.
Convert Next.js bundle analyzer data to NDJSON and explore it
Frontend development skill for React, Next.js, TypeScript, and Tailwind CSS applications. Use when building React components, optimizing Next.js performance, analyzing bundle sizes, scaffolding frontend projects, implementing accessibility, or reviewing frontend code quality.
Optimize web performance: Core Web Vitals (LCP, CLS, INP), bundle size, images, caching. Use when site is slow, optimizing for Lighthouse scores, reducing bundle size, fixing layout shifts, or improving Time to Interactive. Triggers on: web performance, Core Web Vitals, LCP, CLS, INP, FID, bundle size, page speed, slow site.
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for source maps, build manifests, chunk registries, emitted bundles, obfuscated loader flow, and frontend runtime recovery. Use when the user asks to reconstruct served JavaScript structure, inspect source maps or chunk maps, trace bundle loading, recover hidden routes or APIs from emitted assets, or explain runtime behavior from built frontend artifacts. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Performance profiling principles. Measurement, analysis, and optimization techniques.
This skill should be used when the user wants to optimize Next.js frontend performance using Lighthouse, bundle analysis, and animation best practices. Use when diagnosing slow pages, optimizing bundle size, or improving Core Web Vitals (LCP, TBT, CLS).
Investigates hypotheses that MEV activity (bundles, searchers, same-block ordering) temporally overlaps or co-occurs with launch-phase rug signals—using public txs, bundle IDs, and clustering with explicit confidence. Use when the user asks about MEV plus rug coordination, launch sniper bundles, Jito or Flashbots overlap with dev exits, or joint profit-flow case studies—not for alleging collusion without evidence, harassing addresses, or live interference.