发现 documentation architecture patterns 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。
Check Arbtr for architectural decisions before scaffolding features, adding npm dependencies, refactoring code, or making architectural changes. Use this skill when the user asks to add new features, install li...
IBL5 module refactoring using interface-driven architecture pattern with Repository/Service/View separation. Use when refactoring legacy PHP-Nuke modules to modern PHP.
Enforce TapScore backend service layer organization and code quality standards. Use when implementing or modifying service classes, business logic, or database operations. Ensures compliance with service layer...
React best practices, hooks patterns, and component architecture. Use when building React components or debugging React issues. (project)
Testing methodologies, patterns, and best practices for unit, integration, and E2E tests. (project)
RESTful API design principles, patterns, and best practices. Use when building backend APIs. (project)
Phased Implementation Supervisor to coordinate coding and code review subagents. Use this skill when the user has an implentation plan file and wants to execute it phase by phase with build verification, testin...
Create TCC Architecture Decision Records (ADRs) in docs/ADRs for architecture, data, API, security, infra, or compliance decisions. Use when making or changing significant system behavior, contracts, tenancy/RL...
Convert AI fluency into throughput by embedding AI into repeatable workflows with triggers, quality gates, and iteration loops that compound over time.
Turn vague intent into solvable structures with explicit objectives, constraints, success criteria, and clear human vs AI responsibility boundaries.
AI-powered PR Author Agent that transforms Observability Diff Plans into Pull Requests. Use when: (1) Generating instrumentation code from Scout Agent output, (2) Creating OTel configuration, correlation header...
AI-powered RCA Copilot for root cause analysis and incident explanation. Use when: (1) Building incident context retrieval from Neptune and DynamoDB, (2) Implementing evidence ranking and root cause candidate g...
AI-powered PR Author Agent that transforms Observability Diff Plans into Pull Requests. Use when: (1) Generating instrumentation code from Scout Agent output, (2) Creating OTel configuration, correlation header...
AI-powered CI Gatekeeper Agent that enforces observability standards in CI/CD pipelines. Use when: (1) Generating GitHub Actions/Jenkins pipelines for observability gates, (2) Configuring progressive enforcemen...
AI-powered Signal Factory Core for processing observability signals and maintaining the knowledge graph. Use when: (1) Developing Signal Engines (Freshness, Drift, Contract, DQ, Volume, Anomaly), (2) Configurin...
File size limits, decomposition patterns, and component architecture. Load before creating any new files. (project)
Complete guide for creating, publishing, and consuming events in the DeLoNET home network's 33GOD agentic developer pipeline. Built on RabbitMQ with strict type safety via Pydantic, async Python (aio-pika), Fas...
Complete guide for creating, publishing, and consuming events in the DeLoNET home network's 33GOD agentic developer pipeline. Built on RabbitMQ with strict type safety via Pydantic, async Python (aio-pika), Fas...
Meta-skill that orchestrates other skills into intelligent, self-coordinating workflows. Use when complex tasks require multiple skills working together, need automated skill routing based on task analysis, wan...
Spot patterns appearing in 3+ domains to find universal principles
Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions.
Find one insight that eliminates multiple components - "if this is true, we don't need X, Y, or Z"
Local-first codebase search with lexical-first BM25 (89.9% Recall@5), multi-hop research, and built-in project memory. Use for architecture analysis, dependency mapping, code research, and finding patterns acro...
Analyze system-wide impact of changes before making them. Use before modifying shared utilities, changing APIs, or refactoring core functionality.
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。