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Found 329 Skills
Aggressively clean up a codebase by removing AI slop, dead code, weak types, defensive over-engineering, duplication, and legacy cruft. Orchestrates 8 specialized subagents in parallel to deduplicate code, consolidate types, kill unused code, untangle circular dependencies, strengthen weak types, remove unnecessary try/catch, delete deprecated/legacy paths, and strip unhelpful comments. Use when the user asks to 'clean up the codebase', 'remove slop', 'improve code quality', 'remove dead code', 'kill AI slop', 'tighten types', 'remove legacy code', 'deduplicate code', 'DRY this up', 'untangle dependencies', or wants a thorough code quality pass. Also use when the user mentions code smells, technical debt cleanup, or refactoring for clarity — even if they don't use the word 'slop'.
Make your messages unforgettable using the Heath brothers' SUCCESs framework Use when: **Crafting a core message** for a product, campaign, or company that needs to stick; **Presenting complex ideas** to audiences who may forget 90% of what you say; **Writing headlines, taglines, or slogans** that people remember and repeat; **Training or educating** when retention matters more than coverage; **Pitching investors or stakeholders** where one memorable idea beats ten forgettable ones
Manage user expectations during wait times with appropriate loading states — from simple spinners to complex skeleton screens and staggered animations. Perceived performance is often more important than actual load time. Use when designing data-heavy components, handling API calls, building hero sections, or improving the feel of a slow interface.
PPC dayparting — bid scheduling by hour/day, peak shopping times, budget optimization by time slot
· Audit AI-generated code slop: hallucinated APIs, over-abstraction, duplicate code, test theater, noisy comments. Triggers: 'slop', 'AI-generated code', 'cleanup', 'overengineered'. Not for prose (use anti-ai-prose).
End-to-end SGLang SOTA performance workflow. Use when a user names an LLM model and wants SGLang to match or beat the best observed vLLM and TensorRT-LLM serving performance by searching each framework's best deployment command, benchmarking them fairly, profiling SGLang if it is slower, identifying kernel/overlap/fusion bottlenecks, patching SGLang code, and revalidating with real model runs.
Expert at diagnosing and fixing performance bottlenecks across the stack. Covers Core Web Vitals, database optimization, caching strategies, bundle optimization, and performance monitoring. Knows when to measure vs optimize. Use when "slow page load, performance optimization, core web vitals, bundle size, lighthouse score, database slow, memory leak, optimize performance, speed up, reduce load time, performance, optimization, core-web-vitals, caching, profiling, bundle-size, database" mentioned.
Optimize Supabase API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for Supabase integrations. Trigger with phrases like "supabase performance", "optimize supabase", "supabase latency", "supabase caching", "supabase slow", "supabase batch".
Removes AI-generated code slop from git diffs to maintain code quality
Optimize SQL queries, design efficient indexes, and handle database migrations. Solves N+1 problems, slow queries, and implements caching. Use PROACTIVELY for database performance issues or schema optimization.
Remove AI-style code slop from a branch by reviewing diffs, deleting inconsistent defensive noise, and preserving behavior and local style.
iOS debugging and troubleshooting skills. Used when users need to investigate and diagnose issues such as crashes, exceptions, runtime errors, memory leaks, memory growth, unreleased ViewController, UI lag, frame drops, slow startup, etc. Provides crash type identification, root cause analysis, LLDB commands and repair solutions.