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Found 2,297 Skills
Effectue des revues de code complètes des merge requests GitLab, analysant la qualité du code, la sécurité, les performances et les bonnes pratiques. À utiliser quand l'utilisateur dit « code review » ou demande de revoir des merge requests ou d'analyser les changements d'une branche avant fusion.
Reviews Rails pull requests, focusing on controller/model conventions, migration safety, query performance, and Rails Way compliance. Covers routing, ActiveRecord, security, caching, and background jobs. Use when reviewing existing Rails code for quality, conducting a PR review, or doing a code review on Ruby on Rails (RoR) code.
Hardware performance counter skill for low-level CPU analysis. Use when collecting PMU events with perf stat, using the PAPI library, measuring cache miss rates and branch misprediction ratios, computing IPC, or correlating PMU events to source lines. Activates on queries about hardware counters, PMU events, perf stat -e, PAPI, cache miss rate, branch misprediction, IPC measurement, or CPU performance events.
Complete AscendC Operator Verification Testcase Generation - Help users with testcase design. Use this skill when users mention testcase design, generalized testcase generation, operator benchmark, UT testcase, precision testcase, or performance testcase.
Application performance profiling and bottleneck identification — Node.js profiling, Chrome DevTools, flame graphs, memory leak detection, CPU profiling, React rendering performance. Activate on "profiling", "performance bottleneck", "flame graph", "memory leak", "slow app", "CPU profiling", "heap snapshot", "React re-renders", "EXPLAIN ANALYZE", "event loop lag", "clinic.js", "Core Web Vitals". NOT for infrastructure monitoring or observability (use logging-observability), load testing (use a load-testing skill), or database schema optimization.
Designs production-grade RAG pipelines with chunking optimization, retrieval evaluation, and pipeline architecture. Use when building a RAG system, selecting a chunking strategy, choosing a vector database, optimizing retrieval quality, designing embedding pipelines, or evaluating RAG performance with RAGAS metrics.
Building decay and upkeep systems for survival games. Use when implementing timer-based decay, Tool Cupboard patterns (Rust-style protection radius), resource upkeep costs, or server performance management through automatic cleanup. Balances gameplay and server health.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch for Claude Code or Cursor, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
NCU-driven iterative optimization workflow for CUDA/CUTLASS/Triton/CuTe DSL kernels. MANDATORY: every optimization MUST start with NCU profiling, followed by multi-dimensional analysis, then targeted code modification, then re-profiling to verify. Supports roofline, memory hierarchy, warp stalls, instruction mix, occupancy, divergence analysis. Provides implementation-specific code modifications: Native CUDA (launch config, memory patterns, async copy, Tensor Core), CUTLASS (ThreadblockShape, stages, epilogue, schedule policy, alignment), Triton (autotune params, compiler hints, tl.* API patterns), CuTe DSL (threads_per_cta, elems_per_thread, tiled_copy, copy atom, shared memory, warp/cta reduce). Use when optimizing any CUDA kernel performance.
Triage mixed game demo and playtest feedback into a prioritized fix brief, weighted evidence summary, and next artifact recommendation. Use when a team has playtest notes, Steam Playtest responses, creator or streamer demo reactions, survey comments, wishlist/context signals, bug lists, or performance findings and needs to decide what to fix first before the next build, festival, or launch beat, even if they only say "sort our playtest feedback", "what should we fix before Next Fest", "players are confused", "streamers bounced off the demo", or "turn these demo notes into priorities".
Amazon sales volume estimator for sellers and product researchers. Estimate monthly sales and revenue from BSR (Best Seller Rank), ASIN, or keyword. Three modes: (A) BSR Calculator — input BSR + marketplace + price + category to get instant sales estimate, (B) ASIN Lookup — input ASIN to auto-fetch data and estimate sales, (C) Keyword Market Analysis — input keyword to analyze total market size and competition. Works on 12 Amazon marketplaces. No API key required. Use when: (1) estimating how many units a product sells per month, (2) sizing a market or niche opportunity, (3) analyzing competitor sales performance, (4) comparing sales across price points, (5) identifying top sellers vs long-tail distribution.
Single-page SEO audit: deep content quality evaluation using Google's E-E-A-T framework, Helpful Content guidelines, on-page SEO factors, search intent alignment, technical signals, and readability analysis. Fetches GSC performance data for that specific page, crawls the live HTML, evaluates metadata, schema markup, internal linking, content depth, and produces a scored report with actionable fixes. Use this skill whenever the user wants to analyze a specific page or URL — not the whole site. Trigger on: "analyze this page", "audit this URL", "how is this page doing", "evaluate my blog post", "check this landing page", "page SEO", "content quality check", "is this page good enough", "review this page's SEO", "what's wrong with this page", "how can I improve this page", "page analysis", "single page audit", "content audit for [URL]", or any request that names a specific URL/page for SEO evaluation. If the user provides a specific URL (not just a domain), this is likely the right skill — use /seo-analysis for full-site audits instead.