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测试与安全 AI 技能

发现 测试与安全 相关 Skills,比较来源仓库和用途,查看适合你工作流的技能说明。

分类目录: 测试与安全

显示第 18,793–18,816 个,共 81,973 个

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GitHub

pydantic-ai-dependency-injection

existential-birds

Implement dependency injection in PydanticAI agents using RunContext and deps_type. Use when agents need database connections, API clients, user context, or any external resources.

GitHub

watchos-code-review

existential-birds

Reviews watchOS code for app lifecycle, complications (ClockKit/WidgetKit), WatchConnectivity, and performance constraints. Use when reviewing code with import WatchKit, WKExtension, WKApplicationDelegate, WCSe...

GitHub

deepagents-code-review

existential-birds

Reviews Deep Agents code for bugs, anti-patterns, and improvements. Use when reviewing code that uses create_deep_agent, backends, subagents, middleware, or human-in-the-loop patterns. Catches common configurat...

GitHub

receive-feedback

existential-birds

Process external code review feedback with technical rigor. Use when receiving feedback from another LLM, human reviewer, or CI tool. Verifies claims before implementing, tracks disposition.

GitHub

sqlite-vec

existential-birds

sqlite-vec extension for vector similarity search in SQLite. Use when storing embeddings, performing KNN queries, or building semantic search features. Triggers on sqlite-vec, vec0, MATCH, vec_distance, partiti...

GitHub

react-flow

existential-birds

React Flow (@xyflow/react) for workflow visualization with custom nodes and edges. Use when building graph visualizations, creating custom workflow nodes, implementing edge labels, or controlling viewport. Trig...

GitHub

agent-architecture-analysis

existential-birds

Perform 12-Factor Agents compliance analysis on any codebase. Use when evaluating agent architecture, reviewing LLM-powered systems, or auditing agentic applications against the 12-Factor methodology.

GitHub

urlsession-code-review

existential-birds

Reviews URLSession networking code for iOS/macOS. Covers async/await patterns, request building, error handling, caching, and background sessions.

GitHub

pydantic-ai-tool-system

existential-birds

Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.

GitHub

langgraph-architecture

existential-birds

Guides architectural decisions for LangGraph applications. Use when deciding between LangGraph vs alternatives, choosing state management strategies, designing multi-agent systems, or selecting persistence and...

GitHub

12-factor-apps

existential-birds

Perform 12-Factor App compliance analysis on any codebase. Use when evaluating application architecture, auditing SaaS applications, or reviewing cloud-native applications against the original 12-Factor methodo...

GitHub

llm-artifacts-detection

existential-birds

Detects common LLM coding agent artifacts in codebases. Identifies test quality issues, dead code, over-abstraction, and verbose LLM style patterns. Use when cleaning up AI-generated code or reviewing for agent...

GitHub

go-testing-code-review

existential-birds

Reviews Go test code for proper table-driven tests, assertions, and coverage patterns. Use when reviewing *_test.go files.

GitHub

react-flow-implementation

existential-birds

Implements React Flow node-based UIs correctly using @xyflow/react. Use when building flow charts, diagrams, visual editors, or node-based applications with React. Covers nodes, edges, handles, custom component...

GitHub

react-flow-advanced

existential-birds

Advanced React Flow patterns for complex use cases. Use when implementing sub-flows, custom connection lines, programmatic layouts, drag-and-drop, undo/redo, or complex state synchronization.

GitHub

healthkit-code-review

existential-birds

Reviews HealthKit code for authorization patterns, query usage, background delivery, and data type handling. Use when reviewing code with import HealthKit, HKHealthStore, HKSampleQuery, HKObserverQuery, or HKQu...

GitHub

pydantic-ai-model-integration

existential-birds

Configure LLM providers, use fallback models, handle streaming, and manage model settings in PydanticAI. Use when selecting models, implementing resilience, or optimizing API calls.

GitHub

tailwind-v4

existential-birds

Tailwind CSS v4 with CSS-first configuration and design tokens. Use when setting up Tailwind v4, defining theme variables, using OKLCH colors, or configuring dark mode. Triggers on @theme, @tailwindcss/vite, ok...

GitHub

swift-code-review

existential-birds

Reviews Swift code for concurrency safety, error handling, memory management, and common mistakes. Use when reviewing .swift files for async/await patterns, actor isolation, Sendable conformance, or general Swi...

GitHub

review-feedback-schema

existential-birds

Schema for tracking code review outcomes to enable feedback-driven skill improvement. Use when logging review results or analyzing review quality.

GitHub

review-skill-improver

existential-birds

Analyzes feedback logs to identify patterns and suggest improvements to review skills. Use when you have accumulated feedback data and want to improve review accuracy.

GitHub

pydantic-ai-agent-creation

existential-birds

Create PydanticAI agents with type-safe dependencies, structured outputs, and proper configuration. Use when building AI agents, creating chat systems, or integrating LLMs with Pydantic validation.

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。

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