
Test Data Factory (Grade A)用 Claude AI 生成最高级别的安全开发技能。 A 等级。生成单位和整合测试的类型安全测试数据工厂和测试元件。 当用户要求创建模拟数据,测试元件或数据工厂时请使用。
概览
主要功能
- 类型安全工厂功能
- 有理 Defaults
- 易于重写
- 可复用工厂
- 关系处理
- 数据库测试创建
价格
- 模型
- Free
- 分类
- 育言活动
- 评分
- 暂无评价
使用场景
单元测试
使用 Test Data Factory 生成模拟数据进行单元测试,确保可以 isolation 和可靠的测试每个单独的组件。
整合测试
使用 Test Data Factory 创建数据库测试元件测试不同组件如何与数据库和彼此交互。
优点 & 缺点
优点
- 生成的类型安全测试数据工厂
- 提供有理 Defaults 和易于重写
- 支持单位和整合测试
- 可复用工厂函数
- 处理实体之间的关系
缺点
- 需要 TypeScript 和测试框架的知识
- 可能需要为特定数据库或框架进行额外的设置
评测
登录以留下评测。
暂无评测。来当第一个吧!
问答
Why You Should Use This?
| Audience | Key Benefits | | -------------------- | ------------------------------------------------------------------------------------------------- | | Individual | 30%+ token savings, stop repeating standards, security guardrails, instant scaffolding | | Teams | Consistent AI behavior, day-one onboarding, codified patterns, compounding cost savings | | Organizations | Always-on compliance, same standards across 1,000 projects, central governance, measurable ROI |
Asked by Greta Nowak · May 15, 2026
What You Can Customize?
| Section | What It Controls | Example | | ------------- | -------------------------- | ---------------------------------------------- | | project | Project identity | Name, description, repo URL | | techStack | Language, framework, tools | TypeScript + Express or Python + FastAPI | | paths | Directory structure | Where handlers, services, and common code live | | domain | Business entities | Order, Product, Customer + lifecycle states | | patterns | Code patterns | 7-step handler flow, error handling strategy | | testing | Quality gates | 90% coverage, test/lint/type-check commands | | database | DB conventions | Soft delete field, timestamp columns, naming | | packages | Internal packages | @your-org scope, registry URL | | conventions | Git and workflow | Branch prefixes, commit format, PR templates |
Asked by Daniel Schmidt · May 3, 2026
What it detects?
| Category | Signals | | ------------------ | ------------------------------------------------------------------------------------------ | | Language | tsconfig.json, go.mod, Cargo.toml, requirements.txt, pom.xml, file extensions | | Framework | Dependencies in package.json / requirements.txt (React, Express, Django, Spring, etc.) | | Database | ORM configs (prisma/, sequelize, typeorm), .sql files, migration folders | | Testing | jest.config., vitest, pytest, cypress/, playwright.config. | | Infrastructure | Dockerfile, terraform/, cdk.json, serverless.yml, cloud SDK deps | | CI/CD | .github/workflows/, .gitlab-ci.yml, Jenkinsfile |
Asked by Victor Nguyen · May 3, 2026
What's Inside?
| Layer | Count | What It Does | How It's Triggered | | ------------- | ----- | ------------------------------------------------- | ----------------------------------- | | Rules | 47 | Enforces coding standards on every AI interaction | Automatically — always on | | Agents | 62 | Specialized assistants for complex tasks | On demand — /agent-name | | Skills | 50 | Step-by-step guided workflows with checklists | Contextually — when patterns match | | Commands | 37 | Lightweight, token-efficient quick actions | On demand — /command | | Hooks | 12 | Automation scripts in the AI loop | Event-driven — before/after actions | | Templates | 9 | Scaffolding for handlers, components, tests, etc. | Referenced by skills and agents | ---
Asked by Qiu Yan · Apr 10, 2026
How It Works?
Layer 1 — Pre-Processing: Hooks inject project context and block dangerous commands before your prompt reaches the AI. Layer 2 — Rules Engine: 47 always-on rules enforce token efficiency, security, architecture, code standards, database conventions, and testing thresholds. Layer 3 — Specialized Processing: The right component activates — an agent, skill, or command — based on your prompt. Layer 4 — Post-Processing: Hooks validate output, auto-format, scan for secrets, and verify coverage.
Asked by Sanjay Gupta · Apr 7, 2026
提问
育言活动 的替代品

安全试验的数据-AI技能 - Claude AI。A级。即将开始需要与当前工作环境隔离的功能工作,或执行实施计划前-创建隔离的git工作tree

为Claude AI提供了经过安全测试的数据ai技能。 Grade A. GA4 BigQuery导出模式参考 - 完整字段参考、嵌套结构、查询模式和性能提示

安全测试的数据-AI技能,专为Claude AI打造。Grade A. Meta Conversions API (CAPI) 设置指南-架构、事件类型、客户信息哈希、去重复、实现示例、AEM

经过安全测试的 Claude AI 开发技能。Grade A。列出函数/方法调用的直接调用图

安全测试数据-ai技能,Grade A. 名为Haskell测试模块,以同一命名空间中的测试模块命名,并在其后添加 Spec 辅助。 在编写或审阅Haskell测试模块时使用。

经安全检测的数据 AI 技能,适用于 Claude AI。A级。模拟五位专家董事会就重大决策进行审议。用于评估计划、架构选择、功能设计或任何决策。

安全测试的开发技能,适用于 Claude AI。Grade A。通过 PE(入口点)实现高级 MVC —— 在标准 MVC 界面(CNTA300/MATA070/MATA440/MATA460/FINA040 via *STRU)中添加自定义网格。
经过安全测试的 DevOps 技能,适用于 Claude AI。Grade A。**WORKFLOW SKILL** — 在 docs site、agent files 和 changelog 中保持仓库文档的准确性和新鲜度。WHEN: "update docs"




