xunit
xUnit é uma estrutura de testes para agentes de IA
Navegue e instale milhares de habilidades para AI Agents no diretório Killer-Skills. Compatível com Claude Code, Windsurf, Cursor e mais.
xUnit é uma estrutura de testes para agentes de IA
Resumo localizado: $ARGUMENTS should be <roadmap-slug [phase-number]. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.
O agente de IA Claude Code pode ajudar a criar comunicações internas eficazes, incluindo relatórios de status, atualizações de liderança e newsletters da empresa.
Resumo localizado: # metadata file Each skill directory should have .<skill-name .SKILL.md that will contain matadata. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.
Helps users discover and install agent skills when they ask questions like how do I do X, find a skill for X, is there a skill that can..., or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Resumo localizado: # Frontend Responsive This Skill provides Claude Code with specific guidance on how to adhere to coding standards as they relate to how it should handle frontend responsive.
Generate a single-line commit message for ant-design by reading the projects git staged area and recent commit style. Use when the user asks for a commit message, says msg, commit msg, 写提交信息, or wants one-line text that covers all staged changes. Output should match the repositorys existing commit style and summarize all staged changes in one line.
This skill should be used when the user asks to update documentation for my changes, check docs for this PR, what docs need updating, sync docs with code, scaffold docs for this feature, document this feature, review docs completeness, add docs for this change, what documentation is affected, docs impact, or mentions docs/, docs/01-app, docs/02-pages, MDX, documentation update, API reference, .mdx files. Provides guided workflow for updating Next.js documentation based on code changes.
This skill should be used when the user asks to create AGENTS.md, update AGENTS.md, maintain agent docs, set up CLAUDE.md, or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
We should update the version number of the package before release.