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Implement continuous AI iteration loops for complex development tasks. Use when building features requiring test-driven refinement, implementing tasks with clear success criteria, or automating iterative improv...
AI-powered test generation using pattern recognition, code analysis, and intelligent test synthesis for comprehensive test coverage.
O(log n) sublinear coverage gap detection with risk-weighted analysis and intelligent test prioritization.
Security-first visual testing combining URL validation, PII detection, and visual regression with parallel viewport support. Use when testing web applications that handle sensitive data, need visual regression...
Optimized MCP server for QE with connection pooling, O(1) tool lookup, load balancing, and
Requirements traceability, acceptance criteria validation, and BDD scenario management for complete requirements coverage.
Domain-Driven Design architecture for Agentic QE v3. Implements modular, bounded context architecture with clean separation of concerns for quality engineering domains.
Chaos engineering and resilience testing including fault injection, load testing, and system recovery validation.
Transfer learning, metrics optimization, and continuous improvement for AI-powered QE agents.
Deep integration with agentic-flow@alpha for SONA learning, Flash Attention (2.49x-7.47x speedup), and 9 RL algorithms.
Knowledge graph-based code understanding with semantic search and 80% token reduction through intelligent context retrieval.
Unified memory system for QE with AgentDB, HNSW indexing (150x-12,500x faster search), and SONA learning integration.
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...
Migrate Agentic QE projects from v2 to v3 with zero data loss
Migrate Agentic QE projects from v2 to v3 with zero data loss
Visual regression testing, responsive design validation, and WCAG accessibility compliance testing.
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...
专注于查阅、维护和生成项目文档 (位于 docs/ 目录下)。
运行和分析项目质量检查（Linting, 类型检查, 测试）。
暂存更改并生成符合 Conventional Commits 规范的提交消息。
编写、运行和优化项目测试用例（Vitest）。
分析项目上下文、Nuxt 3 结构和依赖项，用于规划和调试。
遵循项目标准生成和修改 Vue 3、TypeScript 和 SCSS 代码。
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...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。