Agent Skills Hub

mutation-testing-js

Mutation testing patterns for JS/TS using Stryker. Analyze branch code to find weak or missing tests, verify test effectiveness, and strengthen Node.js test suites.

ring:testing-skills-with-subagents

A meta-skill for building robust AI agent skills using a TDD approach: define failure (RED), implement the skill (GREEN), and plug rationalization loopholes (REFACTOR).

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.

holistic-testing-pact

Apply Holistic Testing with PACT (Proactive, Autonomous, Collaborative, Targeted) principles to build quality into team culture and test strategies for modern software systems.

long-running-agent

Framework for building AI agents that persist state across multiple context windows, enabling them to complete complex, multi-day coding tasks without losing progress or context.

skill-code-review

Multi-LLM code review pipeline using consensus-based analysis to detect security, architectural, and quality issues.

analysis-phase

Validates cross-artifact consistency (spec, plan, tasks) and detects breaking changes (API, DB, UI) during software feature development.

dotnet-claude-code-skills

A suite of .NET engineering skills for Domain-Driven Design (DDD), EF Core persistence, BDD-style unit testing, and IDE-like semantic code understanding with Serena MCP.

writing-skills

A Test-Driven Development (TDD) framework for writing agent skills, using pressure scenarios to ensure documentation guides agent behavior effectively.

karpathy-guidelines

Behavioral guidelines for LLMs to reduce coding mistakes, follow best practices, and improve output quality by enforcing simplicity, surgical changes, and goal-driven verification.

test-generator

Automated generation of structured, production-ready pytest test suites for Python functions and classes.

project-guidelines-example

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