NeoLabHQ

A comprehensive reference guide for using git worktrees to work on multiple branches simultaneously without stashing changes. It covers creating, managing, and removing worktrees, plus workflow patterns for PR reviews, hotfixes, and comparing implementations across branches.

This skill teaches users how to use git notes to attach metadata to commits without modifying Git history. It covers adding review status, test results, and audit trails to commits, along with sharing notes between team members and preserving notes through rebases.

This skill provides comprehensive guidance for software development following Clean Architecture and Domain-Driven Design principles. It covers code style rules, naming conventions, anti-patterns to avoid, and emphasizes a library-first approach where developers should leverage existing solutions before writing custom code.

A comprehensive reference guide for thought-based reasoning techniques in LLMs. Covers Chain-of-Thought prompting, Zero-shot CoT, Self-Consistency, Tree of Thoughts, ReAct, PAL, and Reflexion with prompt templates, decision matrices, and best practices for improving complex reasoning tasks.

A comprehensive reference guide for understanding and optimizing context in LLM agent systems. Covers context anatomy, degradation patterns, multi-agent verification workflows, and optimization techniques like compaction and observation masking.

A comprehensive evaluation framework for assessing Claude Code agents, commands, and skills. Provides LLM-as-Judge implementation patterns, multi-dimensional rubrics, bias mitigation techniques, and metrics for measuring agent quality across instruction following, completeness, tool efficiency, reasoning, and coherence.

A comprehensive reference guide for designing multi-agent architectures in Claude Code. It covers three main patterns (supervisor/orchestrator, peer-to-peer/swarm, and hierarchical), along with context isolation strategies, consensus mechanisms, failure mode mitigations, and memory system designs ranging from simple file-based to temporal knowledge graphs.

Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.

Use when Code implementation and refactoring, architecturing or designing systems, process and workflow improvements, error handling and validation. Provide tehniquest to avoid over-engineering and apply iterative improvements.

Use when executing implementation plans with independent tasks in the current session or facing 3+ independent issues that can be investigated without shared state or dependencies - dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates

Use when implementing any feature or bugfix, before writing implementation code - write the test first, watch it fail, write minimal code to pass; ensures tests actually verify behavior by requiring failure first