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Found 1,732 Skills
Execute content SEO strategy from keyword research through content planning, writing, and on-page optimization. Use this skill when the user needs to create SEO-optimized content, perform keyword research, identify content gaps, or improve existing content rankings — even if they say 'content strategy', 'keyword research', or 'how to rank for this topic'.
Optimize advertising budget allocation across campaigns using marginal returns analysis. Use this skill when the user needs to distribute budget across multiple campaigns, optimize spend pacing, or maximize overall ROAS under budget constraints — even if they say 'how to split my ad budget', 'campaign budget optimization', or 'diminishing returns on ad spend'.
React Native mobile development. Core components, navigation (React Navigation), platform-specific code, native modules, performance optimization, and debugging. USE WHEN: user mentions "React Native", "react-native", "mobile app with React", "cross-platform mobile", "RN", "react-native-cli" DO NOT USE FOR: Expo-specific features - use `expo`; Flutter - use `flutter`; web React - use `react` skills
When the user wants to optimize delivery routes, solve vehicle routing problems, or minimize transportation costs. Also use when the user mentions "route planning," "delivery optimization," "VRP," "TSP," "multi-stop routing," "route sequencing," or "dispatch optimization." For fleet sizing and management, see fleet-management. For last-mile specific challenges, see last-mile-delivery.
The Quality Score Optimization skill provides a systematic framework for diagnosing, tracking, and improving Quality Score across every keyword in a Google Ads account.
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.
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.
Ultra-lightweight channel for refactor processes - used when changes are clearly too small to go through 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: User says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip the extra steps", and the scope of changes is clearly localized to a single function / single component with test coverage for self-validation.
Product bundling strategy — virtual bundles, multi-pack pricing, cross-sell bundles, bundle listing optimization
Amazon repricing strategy advisor — competitive pricing rules, Buy Box optimization, margin protection, and repricing tool selection. Builds custom repricing logic based on your goals: Buy Box win rate, margin targets, or velocity.
Grafana Professional Services tool for identifying which Prometheus metrics drive high Data Points per Minute (DPM). Analyzes metric-level DPM with per-label breakdown to help optimize Grafana Cloud costs. Use when the user asks about DPM analysis, high-cardinality metrics, metric cost optimization, finding noisy metrics, or running dpm-finder against a Grafana Cloud Prometheus endpoint.
Specializes in analyzing Lynx trace data to diagnose performance issues and provide actionable optimization strategies. Key Scenarios: - Loading Performance: Diagnosing slow startup metrics (FCP, FMP, TTI) and white screen issues. - Smoothness Analysis: Investigating root causes for scroll jank, frame drops, and interaction lag. - Regression Detection: Comparing traces to identify performance degradation or verify optimization gains between versions. - Pipeline Deep Dive: Pinpointing bottlenecks in specific rendering stages like Layout, Paint, JS execution, and background threads. - Native Module Analysis: Investigating performance issues related to native module calls.