skill-creator
Create effective AI skills. This skill should be used when user wants to create a new skill (or update an existing skill) that extends an AI with specialized capabilities, knowledge, workflows, or tool integrat...
Discover Blockchain skills, compare source repositories and read the instructions for each workflow.
Create effective AI skills. This skill should be used when user wants to create a new skill (or update an existing skill) that extends an AI with specialized capabilities, knowledge, workflows, or tool integrat...
Software development lifecycle guidance. This skill should be used when planning development work, conducting code reviews, or establishing development workflows. Use proactively when reviewing code, preparing...
Security guidelines for secure coding and code review. This skill should be used when architecting/designing systems, writing code, or reviewing code. Use proactively when discussing vulnerabilities, OWASP, inj...
Code quality guidelines including naming, structure, and maintainability. This skill should be used when writing or reviewing code to ensure it meets quality standards. Use proactively when discussing naming co...
Review code changes with focus on AI best practices and security
Create consistent releases and changelogs
LiteLLM-RS MCP Gateway Architecture. Covers Model Context Protocol, JSON-RPC 2.0 implementation, multi-transport support (HTTP, SSE, WebSocket, Stdio), and permission system.
LiteLLM-RS A2A Protocol Architecture. Covers Agent-to-Agent communication, JSON-RPC 2.0 messaging, multi-provider orchestration, agent registry, and task state management.
LiteLLM-RS Provider Architecture Guide. Covers 66+ provider integration, trait object design, unified error handling, connection pooling, and LLMProvider trait implementation patterns.
LiteLLM-RS Routing Architecture. Covers 7 routing strategies, lock-free design with DashMap, health-aware selection, fallback chains, and load balancing.
LiteLLM-RS Observability Architecture. Covers Prometheus metrics, OpenTelemetry tracing, structured logging, health checks, and alerting integration.
LiteLLM-RS Provider 开发与架构指南。用于添加新 provider、迁移错误处理、维护 66+ provider 的一致性。包含架构对比分析和最佳实践。
LiteLLM-RS Error Handling Architecture. Covers two-tier error hierarchy, ProviderError factory methods, HTTP status mapping, retry logic, and error context preservation.
LiteLLM-RS Authentication Architecture. Covers JWT + API Key + RBAC multi-method auth, rate limiting with DashMap, middleware pipeline, and secure credential management.
LiteLLM-RS Streaming Architecture. Covers UnifiedSSEParser, SSETransformer trait, VecDeque buffering, provider-specific transformers, and real-time event handling.
LiteLLM-RS Caching Architecture. Covers Redis caching, vector database semantic caching, multi-tier cache strategy, TTL management, and cache invalidation patterns.
LiteLLM-RS Configuration Architecture. Covers YAML loading, environment variable override, validation patterns, type-safe config models, and hot reloading.
Split large tasks into smaller subtasks. Use when a task spans many modules or requires phased implementation.
Execute next task from Implementation Plan. Use when user asks to implement next task, start next feature, or continue implementation.
Add or modify tasks in Implementation Plan. Use when user proposes new requirements, changes priorities, or adjusts existing task scope.
Maintain sloc-guard project documentation. Use when user completes a feature and asks to update docs.
Execute next task from Implementation Plan. Use when user asks to implement next task, start next feature, or continue implementation.
Get the current Neovim context as JSON (cursor position, current file, visual selection and diagnostics) to help answer questions about code at the current cursor position, visual selections and diagnostics. Us...
Utility layer for Kysely on SQLite databases. Use when working with SQLite via Kysely for: schema definition and auto-migration, soft-delete patterns, precompiled queries, pagination, nested transactions using...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.