configure-feature-flags
Check and configure feature flag infrastructure (OpenFeature + providers)
configure-editor
Check and configure EditorConfig and VS Code workspace settings
configure-docs
Check and configure code documentation standards and generators (TSDoc, JSDoc, pydoc, rustdoc)
configure-dockerfile
Check and configure Dockerfile for project standards (minimal Alpine/slim, non-root, multi-stage)
configure-dead-code
Check and configure dead code detection (Knip, Vulture, cargo-machete)
configure-coverage
Check and configure code coverage thresholds and reporting
configure-container
Check and configure container infrastructure (builds, registry, scanning, devcontainer)
configure-claude-plugins
Configure .claude/settings.json and GitHub Actions workflows to use the laurigates/claude-plugins marketplace
configure-cache-busting
Check and configure cache-busting strategies for Next.js and Vite projects
configure-argocd-automerge
Configure auto-merge workflow for ArgoCD Image Updater branches
configure-api-tests
Check and configure API contract testing with Pact, OpenAPI validation, and schema testing
ai-elements-workflow
This skill provides guidance for building workflow visualizations using Vercel AI Elements and React Flow. It should be used when implementing interactive node-based interfaces, workflow diagrams, or process flow visualizations in Next.js applications. Covers Canvas, Node, Edge, Connection, Controls, Panel, and Toolbar components.
betterauth-tanstack-convex
Step-by-step guide for setting up Better Auth authentication with Convex and TanStack Start. This skill should be used when configuring authentication in a Convex + TanStack Start project, troubleshooting auth issues, or implementing sign up/sign in/sign out flows. Covers installation, environment variables, SSR authentication, route handlers, and the expectAuth pattern.
convex-actions-general
This skill should be used when working with Convex actions, HTTP endpoints, validators, schemas, environment variables, scheduling, file storage, and TypeScript patterns. It provides comprehensive guidelines for function definitions, API design, database limits, and advanced Convex features.
Convex Agents Context
Customizes what information the LLM receives for each generation. Use this to control message history, implement RAG context injection, search across threads, and provide custom context.
Convex Agents Debugging
Troubleshoots agent behavior, logs LLM interactions, and inspects database state. Use this when responses are unexpected, to understand context the LLM receives, or to diagnose data issues.
Convex Agents Files
Handles file uploads, image attachments, and media processing in agent conversations. Use this when agents analyze images, process documents, or generate files.
Convex Agents Fundamentals
Sets up and configures Convex agents for chat-based AI interactions. Use this when initializing agent instances, creating conversation threads, and generating basic text or structured responses from LLMs. Essential foundation for any Convex agent implementation.
Convex Agents Human Agents
Integrates human agents into automated workflows for human-in-the-loop interactions. Use this when humans need to respond alongside AI agents, handle escalations, or provide context that AI cannot determine.
Convex Agents Messages
Sends, saves, retrieves, and manages messages within agent conversations. Use this when handling user messages, displaying conversation history, and working with UIMessages for rich rendering.
convex-queries
This skill should be used when implementing Convex query functions. It provides comprehensive guidelines for defining, registering, calling, and optimizing queries, including pagination, full text search, and indexing patterns.
convex-tanstack
Comprehensive guide for building full-stack applications with Convex and TanStack Start. This skill should be used when working on projects that use Convex as the backend database with TanStack Start (React meta-framework). Covers schema design, queries, mutations, actions, authentication with Better Auth, routing, data fetching patterns, SSR, file storage, scheduling, AI agents, and frontend patterns. Use this when implementing features, debugging issues, or needing guidance on Convex + TanStack Start best practices.
vercel-ai-elements
This skill provides comprehensive documentation for all 23 Vercel AI Elements components organized by category (Message, Conversation, Input/Interaction, Content Display, AI Processing, Advanced Features). Use when users ask about building AI chatbots, need component documentation, want API references for Vercel AI Elements, or need integration examples with the AI SDK.
Convex Agents Playground
Sets up a web UI for testing, debugging, and developing agents without code. Use this to manually test agents, browse conversation history, and verify behavior in real-time.
Convex Agents RAG
Implements Retrieval-Augmented Generation (RAG) patterns to enhance agents with custom knowledge bases. Use this when agents need to search through documents, retrieve context from a knowledge base, or ground responses in specific data.
Convex Agents Rate Limiting
Controls message frequency and token usage to prevent abuse and manage API budgets. Use this to implement per-user limits, global caps, burst capacity, and token quota management.
Convex Agents Streaming
Streams agent responses in real-time to clients without blocking. Use this for responsive UIs, long-running generations, and asynchronous streaming to multiple clients.
Convex Agents Threads
Manages conversation threads to group messages into linear histories. Use this when organizing multi-turn conversations, managing per-user history, and handling thread metadata.
Convex Agents Tools
Enables agents to call external functions, APIs, and database operations through tool definitions. Use this when agents need to fetch data, perform actions, or integrate with external services while maintaining clean separation.
Convex Agents Usage Tracking
Tracks LLM token consumption and usage metrics for billing, monitoring, and optimization. Use this to log token usage, calculate costs, generate invoices, and understand which agents or users consume the most resources.
Convex Agents Workflows
Orchestrates multi-step agent operations with durable execution, automatic retries, and recovery from failures. Use this for complex workflows that need to survive server restarts or coordinate multiple agents.
convex-mutations
This skill should be used when implementing Convex mutation functions. It provides comprehensive guidelines for defining, registering, calling, and scheduling mutations, including database operations, transactions, and scheduled job patterns.
godot-product-polisher
Godot 产品美化与打磨专家，支持自然语言描述自动完成视觉效果增强、音效优化、用户体验改进、成品包装等美化工作
skill-creator
创建高效技能的指南。当用户希望打造新的技能（或改进现有技能），以专项知识、工作流或工具集成来扩展 Claude 能力时，请使用本技能。
mcp-orchestration
智能编排和协调多个MCP工具完成复杂开发任务，支持串行、并行、条件、循环等多种执行模式
Chinese Development Guide
为中文开发者提供完整的项目本地化、环境配置和开发工作流指导，确保中英文双语环境下的最佳开发体验
Context7 Auto Research
自动使用Context7进行文档研究，当用户需要代码生成、配置步骤或库/API文档时无需明确请求即可自动获取最新信息
Godot Compatibility Checker
自动检测和修复Godot 3.x与4.x之间的API兼容性问题，基于实际项目经验提供针对性解决方案
MCP Orchestration
智能编排和协调多个MCP工具完成复杂开发任务，支持串行、并行、条件、循环等多种执行模式
godot-mcp-auto-launcher
使用此技能自动启动Godot MCP服务器，确保在Godot项目启动时MCP工具可用。当需要确保MCP连接就绪或在项目启动时自动初始化MCP工具时触发。
godot-performance-optimizer
Godot 性能优化与适配专家，支持自然语言描述自动完成分辨率适配、性能分析、内存优化、帧率提升等优化工作
godot-project-creator
智能化 Godot 项目创建与场景管理技能，支持自然语言描述自动生成完整项目架构
Godot Resource Workflow
提供完整的Godot资源文件（.tres）管理能力，支持资源创建、修改、批量处理和依赖关系管理，优化资源工作流
godot-test-debugger
Godot 测试与调试工作流专家，支持自然语言描述自动完成单元测试、集成测试、错误诊断、性能调试等测试工作
godot-ui-designer
Godot UI界面系统开发专家，支持自然语言描述自动创建菜单、HUD、对话框、响应式布局等完整UI系统
godot-skills
Godot技能统一入口，根据用户需求智能选择并调用最适合的Godot子技能，提供15个专业技能的一站式开发体验
chinese-dev-guide
为中文开发者提供完整的项目本地化、环境配置和开发工作流指导，确保中英文双语环境下的最佳开发体验
context7-auto-research
自动使用Context7进行文档研究，当用户需要代码生成、配置步骤或库/API文档时无需明确请求即可自动获取最新信息
gdscript-syntax-guide
GDScript 语法权威指南，提供最新 Godot 4.5 语法规范、最佳实践、缩进规则和代码风格
godot-animation-studio
Godot 资源与动画创建专家，支持自然语言描述自动完成精灵导入、动画配置、特效制作、音效集成等资源工作
Page 761 of 1486 · 74267 results
