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Found 1,732 Skills
React 19+ patterns, performance optimization, and component architecture. Covers hooks, state management decision trees, data fetching with use() API, Server Components, React Compiler, bundle optimization, and re-render elimination. Use when building components, optimizing re-renders, fetching data, managing state, handling forms, structuring frontends, or reviewing React code.
Provides AWS Lambda integration patterns for TypeScript with cold start optimization. Use when deploying TypeScript functions to AWS Lambda, choosing between NestJS framework and raw TypeScript approaches, optimizing cold starts, configuring API Gateway or ALB integration, or implementing serverless TypeScript applications. Triggers include "create lambda typescript", "deploy typescript lambda", "nestjs lambda aws", "raw typescript lambda", "aws lambda typescript performance".
Mac cleanup & optimization tool combining CleanMyMac, AppCleaner, DaisyDisk features. Deep cleaning, smart uninstaller, disk insights, and project artifact purge.
Next.js App Router best practices — file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling. Use when writing, reviewing, or debugging Next.js App Router code.
Swift 6.2 and SwiftUI performance optimization for iOS 26 clinic architecture codebases. Covers async/await concurrency patterns, Sendable/actor isolation, view/render performance, and animation performance while preserving modular MVVM-C boundaries across App, Feature, Domain, and Data layers. Use when profiling or optimizing Swift/SwiftUI behavior in clinic modules.
Analyze project dependencies for vulnerabilities, updates, and optimization opportunities. Use when auditing dependencies or managing package versions.
Use when Glean MCP tools are available and you need guidance on which tool to use, how to format queries, or best practices for enterprise search. This skill provides tool selection logic and query optimization for Glean integrations. Auto-triggers when mcp__glean tools are being considered.
Complete Convex development mastery — functions (queries, mutations, actions, HTTP actions), schema design, index optimization, argument/return validation, authentication, security patterns, error handling, file storage, scheduling, crons, aggregates, OCC handling, denormalization, TypeScript best practices, and production-ready code organization. The definitive Convex skill. Use when building any Convex backend: writing functions, designing schemas, optimizing queries, handling auth, adding real-time features, setting up webhooks, scheduling jobs, managing file uploads, or reviewing/fixing Convex code. Triggers on: convex, query, mutation, action, ctx.db, defineSchema, defineTable, v.id, v.string, v.object, withIndex, ConvexError, internalMutation, httpAction, ctx.scheduler, ctx.storage, OCC, convex best practices, convex functions, convex schema, convex performance, "how do I do X in Convex".
Optimize and convert images using the optimo CLI and API on top of ImageMagick. Use when the user mentions reducing image size, image compression, batch image optimization, converting formats (jpeg/png/webp/avif/heic/jxl), resizing by percentage/dimensions/max-size, or running optimo in scripts.
PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.
Comprehensive vitest testing patterns covering test structure, AAA pattern, parameterized tests, assertions, mocking, test doubles, error handling, async testing, and performance optimization. Use when writing, reviewing, or refactoring vitest tests, or when user mentions vitest, testing, TDD, test coverage, mocking, assertions, or test files (*.test.ts, *.spec.ts).
A cognitive framework based on learning first principles, providing learning method diagnosis, efficiency assessment, and optimization advice. Use when: (1) Diagnosing if current learning methods align with first principles, (2) Evaluating learning plan efficiency and time investment, (3) Analyzing learning behavior problems and providing improvement suggestions, (4) Determining if learning content is worth the time investment. Core principle chain: Self-learning → Induction → Self-output → Expression restructuring → Logical understanding → Practice.