Agent Skills Hub

rag-implementation

Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.

context-detection

Systematic project technology stack detection, framework-specific skill auto-loading, and multi-stack analysis for fullstack projects like React + Go.

lint-fix

Automated code maintenance loop using Trunk to perform linting, formatting, and iterative error resolution.

session-memory

Enables cross-session context persistence for Claude Code, managing history, project decisions, and workflow patterns to ensure seamless task continuation.

hunt-focus-definition

Synthesize research on system internals and adversary tradecraft into a concrete, testable hunt hypothesis.

evaluation

Build systematic evaluation frameworks for AI agents using multi-dimensional rubrics, LLM-as-a-judge, and regression testing to measure performance, quality, and context engineering effectiveness.

webf-quickstart

Get started with WebF development: setup WebF Go, initialize Vite-based web projects (React/Vue/Svelte), and preview apps in a W3C-compliant native runtime.

implement-type-annotations

Automates the integration of Python and TypeScript type hints to enhance IDE intellisense, error detection, and AI code comprehension.

subagent-driven-development

Execute implementation plans using isolated subagents for each task, featuring a rigorous two-stage review process for spec compliance and code quality.

nango-esm-migration

Fixes CJS/ESM module compatibility issues in Nango integrations after zero-yaml migration, including path adjustments, ESM wrappers, and restoring original implementations.

paper-reproduce

Systematic methodology for reproducing published academic papers using provided data, including sample selection, statistical verification, and automated reporting.

wenxian

Automated academic literature retrieval, structured summarization, and multi-channel scheduling workflow for research topics.