nlx-design-stack
Use when designing AI agents or chatbots, when raw model outputs feel like a black box, or when building natural language interfaces that need structure and trust
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Use when designing AI agents or chatbots, when raw model outputs feel like a black box, or when building natural language interfaces that need structure and trust
Use when AI agents frequently hit dead ends, when reliability is the main constraint on scaling utility, or when general model improvements don't solve specific blockers
Use when designing AI agent products, defining roadmaps for agentic workflows, or evaluating how to evolve AI from passive tool to proactive partner in software development
Use when building AI-powered products or agents, when raw model intelligence isn't enough to solve user problems, or when designing the architecture for agentic workflows
Use when designing futuristic agentic workflows, when wanting AI to proactively act on team communications, or when eliminating the bottleneck of formal specifications
This skill should be used when the user asks to "collaborate with Codex", "use Codex for planning", "get Codex review", "delegate to Codex", "Codexと協調", "Codexにレビューを依頼", "Codexに計画を作成させたい",...
Document learnings, capture repeatable workflows as skills, and prepare to compound an opence change.
Coordinate prompt and skill updates across related changes
Create a concise plan. Use when a user explicitly asks for a plan related to a coding task.
This skill should be used when the user asks to "find past conversations", "recall what was done", "search history", "look up previous work", "how did we handle X", "what was that implementation", "find similar...
Web search with automatic Qdrant storage for building persistent knowledge
Build Retrieval-Augmented Generation systems with vector databases
Build specialized sub-agents for the workflow system
Patterns for ingesting knowledge into vector databases and RAG systems
Create and manage reusable prompt templates
Break down complex tasks into actionable, atomic steps that can be executed by individual agents.
Compare and evaluate embedding models for semantic search
AI video generation patterns using Sora, Runway, Pika, and other AI video tools. Use when generating videos from text prompts, image-to-video conversion, AI video editing, or integrating AI video APIs.
Store and retrieve documents using Qdrant for RAG workflows. Use for persistent memory, research storage, and semantic search.
Patterns for wrapping any agent with RAG context from Qdrant. Use to add persistent memory to imported or external agents.
Build Model Context Protocol servers for Claude Code integration
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or to...
Conduct comprehensive, multi-source research on any topic using web search, documentation lookup, and critical analysis. This skill should be used when users request thorough investigation, deep research, or co...
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.