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Found 1,578 Skills
React 19 patterns with React Compiler. Automatic optimization, Server Components, use() hook. Trigger: When building React components, using hooks, working with forms, or server/client components.
Think like Intel's legendary CEO. Apply Andy Grove's management operating system to maximize your team's output through leverage, OKRs, and systematic decision-making. Use when: **Scaling a team** when individual contribution isn't enough; **Performance management** to measure and improve output; **Meeting optimization** to make meetings productive; **Decision-making** in management contexts; **New manager transition** from individual contributor
Create, optimize, and iteratively refine agent prompts and system prompts. Use when asked to "improve a prompt", "optimize a system prompt", "rewrite an agent prompt", "tune prompt wording", "make this prompt more reliable", or "adapt a prompt for OpenAI, Claude, or Gemini". Handles model-specific prompt guidance, prompt markers/tags, eval design, and meta optimization loops for new and existing prompts.
MUST be used whenever optimizing a Dune app for speed, reducing render counts, improving CDF query efficiency, or reducing bundle size. Do NOT skip measurement steps — always profile before changing code. Triggers: performance, slow, laggy, optimize, optimization, re-render, bundle size, load time, Lighthouse, profiler, virtualization, lazy load, code split, CDF query, large list, memory leak.
cuTile Python DSL kernel implementation patterns, CtKernel runtime wrapper, suitability gate, and cuTile-specific pitfalls. Use when: (1) creating or modifying a cuTile Python DSL kernel version, (2) implementing an optimization that still fits within cuTile's exposed control surface, (3) deciding whether cuTile is still the right DSL, (4) reviewing cuTile-specific runtime patterns. Always also load /design-kernel for shared naming, versioning, and workflow.
Ultra-lightweight channel for refactor processes - used when changes are obviously too small to justify the full scan → design → apply three-stage workflow. AI directly identifies 1-3 low-risk optimization points, confirms with the user once, modifies in-place using classic methods, and validates itself by running tests. No scan checklist, no design documentation, no multi-step HUMAN verification required. Trigger scenarios: When the user says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip all those steps", and the scope of changes is clearly limited to a single function/single component, with tests available for self-validation.
Plan and optimize Amazon Sponsored Display campaigns. Audience targeting, product targeting, retargeting strategy, and creative optimization for awareness and conversion.
Enter this sub-process when conducting code optimization — handle tasks where 'behavior remains unchanged, structure changes' (structure / performance / readability). Shift single-module internal optimization from 'AI random refactoring' to 'first scan to generate a checklist, confirm each item with the user, execute step-by-step according to the method library, and require manual approval for each step'. Trigger scenarios: Users mention phrases like 'optimize it / refactor / rewrite / split it / poor performance / code is too long' without any accompanying behavior changes. Do not handle new requirements (route to feature), bugs (route to issue), or cross-module architecture restructuring (route to architecture + decisions).
There's an AI for That (TAAFT) platform help — #1 AI tools directory (42,000+ tools, 3-4M monthly visits, DR76 dofollow, 1M+ newsletter subscribers). Covers tool submissions ($347 paid, free monthly X thread), featured PPC ads (bid-based positioning), highlighted listings, listing optimization, $300 TAAFT-first launch bonus, newsletter inclusion, and ChatGPT plugin API. Use when submitting an AI tool to TAAFT, wondering if the $347 listing is worth it, trying to get featured on TAAFT, want to optimize your TAAFT listing for clicks, comparing TAAFT with Futurepedia or Altern, or need to understand TAAFT's PPC ad system. Do NOT use for multi-directory launch coordination (use /sales-launch-directory). Do NOT use for other AI directories like Altern (use /sales-altern) or Futurepedia (use /sales-futurepedia).
A repository of BigQuery-specific logic, knowledge, and specialized standards. Use this skill whenever you are doing anything with BigQuery, including: 1. BigQuery query optimization 2. BigFrames Python code 3. BigQuery ML/AI functions.
Implement AI Coaching best practices on AnalyticDB for PostgreSQL (ADBPG): Leverage Supabase projects (training data management) + ADBPG instances with vector optimization to build RAG-driven coaching systems that guide users through domain-specific workflows, decision-making, or skill development. Use when: User wants to create Supabase projects (spb-xxx), ADBPG instances (gp-xxx), vector knowledge bases, or RAG-driven coaching systems on ADBPG. Triggers: "Supabase", "ADBPG", "vector database", "knowledge base", "RAG", "AI coaching", "coaching system", "spb-xxx", "gp-xxx"
Hands-on short-video editing coach covering the full post-production pipeline, with mastery of CapCut Pro, Premiere Pro, DaVinci Resolve, and Final Cut Pro across composition and camera language, color grading, audio engineering, motion graphics and VFX, subtitle design, multi-platform export optimization, editing workflow efficiency, and AI-assisted editing.