Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
572 skills found
Apply the Six Thinking Hats methodology to software testing for structured, comprehensive quality analysis, test strategy design, and team discussions.
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).
Provides expert technical guidance for analyzing, parsing, and debugging DWARF format debug information in compiled binaries.
Structured, template-driven workflow for end-to-end feature development including coding, automated testing, verification, and session-based improvement.
Transform text into professional Mermaid diagrams. Automatically handles syntax, subgraphs, and layout rules for clean flowcharts, sequence diagrams, and process maps.
Generates UI components, hero sections, and feedback forms with integrated accessibility checks, leveraging specialized design references and quality gates.
Expert guidance for designing and implementing high-quality tool schemas and descriptions for Julia's agent systems, ensuring reliable tool execution and reducing model hallucinations.
Research agent for Nia: index/search remote codebases, docs, and packages. Optimizes AI context by prioritizing full source indexing over web fetches to reduce hallucinations.
Foundational guidelines for context engineering: optimizing token budgets, attention mechanics, and system architecture for AI agents.
Generates comprehensive, best-practice unit tests for functions and classes, supporting multiple frameworks like pytest, unittest, and jest.
Token-efficient codebase analysis skill for call graphs, semantic search, impact analysis, and data flow. Saves ~95% tokens vs. raw reads.
A professional code quality suite for software engineers, implementing SOLID principles, design patterns, refactoring techniques, and technical debt management to ensure clean, maintainable, and production-ready code.