Agent Skills Hub

conversion-psychology

Psychology of conversion for video and sponsored content. Uses emotional triggers, social proof, scarcity, and persuasion principles to optimize scripts and enhance audience engagement.

moai-foundation-core

Foundational architectural principles for MoAI-ADK, featuring TRUST 5, SPEC-First TDD, delegation patterns, and token-efficient agent orchestration workflows.

pattern-detection

Analyze and identify codebase patterns (naming, architecture, testing) to maintain consistency and enforce standards during development.

serena

Symbol-level code understanding and navigation agent toolkit using LSP for precise code analysis, reference tracking, and surgical refactoring across 30+ programming languages.

javascript-typescript

Advanced TypeScript and React development assistant for modern web applications. Expert in component architecture, state management, Vitest unit testing, Playwright E2E automation, and efficient TypeScript configuration.

stock-analyzer

Perform comprehensive technical analysis for stocks and ETFs using indicators like RSI, MACD, and Bollinger Bands to generate actionable trading signals and comparative reports.

refactoring-patterns

Safely refactor code to improve structure and maintainability while preserving behavior through TDD cycles and automated test verification.

synapse

Autonomous pattern detection and skill recommendation engine that monitors project memory, logs, and task lists to evolve your AI agent's capabilities automatically.

screenshots

Automate the generation of high-quality, HiDPI marketing screenshots for web applications using Playwright.

swarm-advanced

Orchestrate complex multi-agent swarms with topologies like mesh, hierarchical, and star for research, development, and testing workflows.

interpreting-culture-index

Interprets Culture Index (CI) surveys and behavioral profiles. Analyzes team composition, burnout risk, and hiring profiles using data-driven trait assessment.

context-optimization

Optimize agent context windows through KV-caching, observation masking, summarization-based compaction, and context partitioning to reduce costs and latency.