Agent Skills Hub

security-review

A comprehensive security auditing and hardening assistant that applies best practices for authentication, input validation, secrets management, and SQL injection prevention to your codebase.

write-e2e-cases

Automate the creation and maintenance of Rsbuild E2E tests, ensuring feature coverage and regression prevention through Playwright.

upstash-vector-db-skills

Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.

moai-foundation-core

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

implement-feature

Guide for implementing features using architecture-first design, TDD, rich domain models, and Swift 6.2 patterns, ensuring a clean separation between Domain, Infrastructure, and App layers.

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.

static-site-generation

A framework for managing static site generator (SSG) projects using Astro, including build optimization, GitHub Pages deployment patterns, and type-safe content collection schemas.

weather-bot

Provides real-time weather forecasts and personalized clothing recommendations for any city using wttr.in.

bear-notes

Manage and automate your Bear notes on macOS using the grizzly CLI tool.

golang-cli-review

Expert automated code review for Go CLI applications, focusing on Cobra/urfave patterns, security, performance, idiomatic Go, and robust error handling.

shift-left-testing

Accelerate software delivery by shifting testing to the earliest development phases, using AI-driven requirements validation, TDD, and automated CI pipelines to reduce defect costs.

llmfit-advisor

Analyze local system hardware (RAM, CPU, GPU/VRAM) to receive expert recommendations for optimized local LLM models, quantization settings, and performance estimates.