Agent Skills Hub

libragent-quality

Comprehensive code quality validation for LibrAgent, covering TypeScript frontend and Rust/Tauri backend via automated linting, formatting, type checking, and build verification.

using-git-worktrees

Creates isolated git worktrees for parallel development, automatically handling directory selection, .gitignore safety checks, dependency installation, and baseline test verification.

dgame-dev

Expert assistant for the DGame Unity framework, facilitating development, architecture, hotfix, and resource management within the TEngine-based ecosystem.

security-audit

Automated security validation, RLS enforcement, OWASP compliance, and vulnerability scanning for AI-assisted development workflows.

orchestrate

Multi-phase feature development workflow for complex tasks using research, planning, implementation, and review gates.

creating-agents-md

Provides a standardized template and guidelines for creating agents.md files to deliver project-specific context to AI coding assistants.

state-management

Guidance on frontend state management, including global stores like Zustand/Pinia, server state via TanStack Query, and URL state handling.

deep-thinking

A deep reasoning protocol that ensures systematic analysis, multi-hypothesis generation, and rigorous verification for complex architectural, debugging, and high-stakes tasks.

acceptance-testing

Plan, implement, and execute user acceptance tests (UAT) and end-to-end scenarios to validate requirements against user-visible behavior.

trulens-evaluation-workflow

A systematic workflow to instrument, evaluate, and monitor LLM applications using TruLens, supporting frameworks like LangChain, LangGraph, and LlamaIndex.

manufacturing-failure-reason-codebook-normalization

Normalizes testing defect logs by correcting typos, abbreviations, and ambiguous descriptions based on product-specific codebooks and station validation.

exploratory-testing-advanced

Advanced exploratory testing with SBTM, RST heuristics, and test tours. Use for investigating bugs, discovering unknown risks, and structured manual exploration.