Agent Skills Hub

bdg

A terminal-based Chrome DevTools Protocol client designed for AI agents. Provides direct, session-persistent control over browser navigation, DOM manipulation, scraping, and network inspection.

ReasoningBank Intelligence

Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement in AI agents.

refly

Base ecosystem skill for Refly. Creates, discovers, and runs domain-specific skills, routes user intent to workflows via symlinks, and automates multi-step pipelines via the Refly CLI.

plan

Structured 6-phase workflow for planning and implementing features, skills, and architectural changes with automated tool discovery and safety verification.

aws-solution-architect

Expert AWS solution architecture for startups focusing on serverless, scalable, and cost-effective cloud infrastructure with modern DevOps practices and IaC.

gemini-interactions-api

Expert skill for implementing the Gemini Interactions API. Use for stateful multi-turn chat, background Deep Research agent tasks, function calling, structured outputs, and modern Python/TypeScript SDK integration.

ui-ux-reviewer

Analyze UI/UX quality against 4 authoritative standards (NNg, Laws of UX, Apple HIG, WCAG) to receive actionable design and accessibility improvements for mobile and web components.

solve-challenge

A CTF solver agent that performs triage on challenges, identifies the vulnerability category, and routes tasks to specialized skills for web, pwn, crypto, forensic, and reverse engineering analysis.

supermemory

Supermemory is a long-term memory infrastructure for AI agents, enabling persistent context, user profiles, and semantic RAG across multi-modal knowledge bases.

tanstack-integration-best-practices

Integration patterns and best practices for TanStack Query, Router, and Start. Ensures type-safe data flow, efficient SSR, and unified caching.

Delegating to AWS Agent

Implement an AI agent delegation architecture to keep your main context clean, reduce token costs, and isolate specialized infrastructure or API tasks.

update-llm-model-list

Audit and synchronize the supported LLM model list in assets.py against the authoritative litellm registry.