GitHub
qe-requirements-validation
Requirements traceability, acceptance criteria validation, and BDD scenario management for complete requirements coverage.
☆ 216Voir le skill
Skills IA Contenu et médias
Découvrez les skills Contenu et médias, comparez leurs dépôts et consultez leurs instructions.
Catégories: Contenu et médias
Contenu et médias Effacer les filtres
Explorer
GitHub
v3-qe-ddd-architecture
Domain-Driven Design architecture for Agentic QE v3. Implements modular, bounded context architecture with clean separation of concerns for quality engineering domains.
☆ 216Voir le skill
GitHub
qe-chaos-resilience
Chaos engineering and resilience testing including fault injection, load testing, and system recovery validation.
☆ 216Voir le skill
GitHub
qe-learning-optimization
Transfer learning, metrics optimization, and continuous improvement for AI-powered QE agents.
☆ 216Voir le skill
GitHub
v3-qe-agentic-flow-integration
Deep integration with agentic-flow@alpha for SONA learning, Flash Attention (2.49x-7.47x speedup), and 9 RL algorithms.
☆ 216Voir le skill
GitHub
qe-code-intelligence
Knowledge graph-based code understanding with semantic search and 80% token reduction through intelligent context retrieval.
☆ 216Voir le skill
GitHub
v3-qe-memory-unification
Unified memory system for QE with AgentDB, HNSW indexing (150x-12,500x faster search), and SONA learning integration.
☆ 216Voir le skill
GitHub
sfdipot-product-factors
James Bach's HTSM Product Factors (SFDIPOT) analysis for comprehensive test strategy generation. Use when analyzing requirements, epics, or user stories to generate prioritized test ideas across Structure, Func...
☆ 216Voir le skill
GitHub
aqe-v2-v3-migration
Migrate Agentic QE projects from v2 to v3 with zero data loss
☆ 216Voir le skill
GitHub
aqe-v2-v3-migration
Migrate Agentic QE projects from v2 to v3 with zero data loss
☆ 216Voir le skill
GitHub
qe-visual-accessibility
Visual regression testing, responsive design validation, and WCAG accessibility compliance testing.
☆ 216Voir le skill
GitHub
test-idea-rewriting
Transform passive 'Verify X' test descriptions into active, observable test actions. Use when test ideas lack specificity, use vague language, or fail quality validation. Converts to action-verb format for clea...
☆ 216Voir le skill
GitHub
documentation-specialist
专注于查阅、维护和生成项目文档 (位于 docs/ 目录下)。
☆ 215Voir le skill
GitHub
quality-guardian
运行和分析项目质量检查（Linting, 类型检查, 测试）。
☆ 215Voir le skill
GitHub
conventional-committer
暂存更改并生成符合 Conventional Commits 规范的提交消息。
☆ 215Voir le skill
GitHub
test-engineer
编写、运行和优化项目测试用例（Vitest）。
☆ 215Voir le skill
GitHub
context-analyzer
分析项目上下文、Nuxt 3 结构和依赖项，用于规划和调试。
☆ 215Voir le skill
GitHub
nuxt-code-editor
遵循项目标准生成和修改 Vue 3、TypeScript 和 SCSS 代码。
☆ 215Voir le skill
GitHub
create-serena-memory-for-component
为任意组件或模块创建/更新 Serena memory 的工作流与格式规范。用于用户要求“源码级梳理并写入 Serena memory”的场景，例如“对 X 进行源码级梳理并写入 Y.md”，或者“分析 X 并生成Serena memory”。适用于组件类/接口名或模块...
☆ 214Voir le skill
GitHub
cpp-interface-purpose-comments
Add a standard Purpose comment above each pure virtual method declaration in C++ interface header files (.h/.hpp). Use when asked to batch annotate interface classes or enforce a consistent comment block above...
☆ 214Voir le skill
GitHub
test-driven-development
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 fir...
☆ 214Voir le skill
GitHub
analyze-project
Analyze a project's codebase and documentation to generate coding standards, architecture docs, and development practices. Perfect for new project onboarding. Usage: 'analyze-project: /path/to/project' or 'anal...
☆ 214Voir le skill
GitHub
memory
Save and recall information across sessions. Use when you hear 'remember this', 'save to memory', 'add to your knowledge', or similar. Stores to Claude OS knowledge bases for persistent recall.
☆ 214Voir le skill
GitHub
code-quality
Analyze code quality using ESLint and project-specific patterns
☆ 214Voir le skill
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.