Agent Skills Hub

design

Collaborative UI design, wireframing, and Tailwind-first code polish to build distinctive, high-quality interfaces without AI slop.

Observability

Real-time observability dashboard for PAI multi-agent activity, featuring live WebSocket streaming, session tracing, and agent workflow debugging.

project-guidelines-example

A project-specific template skill providing standardized architecture, file structures, coding patterns, and deployment workflows for production-grade AI applications.

generate-sdk-types

Automates TypeScript type generation from Rust tool schemas to ensure end-to-end type safety between server and client in MCP-based projects.

Global Validation

Implement robust server-side and client-side input validation using sanitization and allowlists to prevent injection attacks and ensure data integrity.

debugging

Standardized debugging and diagnostic guidelines for AI coding agents.

build-design-system

Build a cohesive, constraint-based design system using the Design Graph methodology. Automate the creation of design tokens, typography scales, components, variants, and themes.

deepscan-monitor

Manage long-running PapersFlow DeepScan research workflows with asynchronous monitoring, live progress tracking, and automated report generation.

parallel-agents

Orchestrate complex workflows by coordinating multiple specialized AI agents for multi-perspective code analysis, feature implementation, and system-wide reviews.

design-system-implementation

Enforce strict UI adherence to your project's design system tokens, components, and layout patterns for consistent frontend implementation.

backend-development

Build, optimize, and maintain production-ready backend systems using Node.js, Python, Go, and Rust. Includes API design, database management, security, and DevOps best practices.

context-optimization

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