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Found 84 Skills
Create, improve, and test skills for the z-schema JSON Schema validator library. Use this skill whenever the user wants to create a new skill from scratch, turn a workflow into a reusable skill, update or refine an existing skill, write test cases for a skill, or organize reference material for a skill. Also use when someone mentions "skill", "SKILL.md", or wants to document a z-schema workflow for reuse by humans or AI agents.
Use this skill when you need to operate the Creem CLI for authentication checks, products, customers, checkouts, subscriptions, transactions, configuration, monitoring, or terminal automation workflows. Prefer it for agent-driven Creem tasks that should use real CLI commands and JSON output instead of dashboard clicks or guessed API calls.
Command-line interface for CloudAnalyzer — Agent-friendly harness for CloudAnalyzer, a QA platform for mapping, localization, and perception outputs. Supports 27 commands across 8 groups: point cloud evaluation, trajectory evaluation, ground segmentation QA, config-driven quality gates, baseline evolution, processing, visualization, and interactive REPL.
Guide for creating effective skills for AI coding agents working with Azure SDKs and Microsoft Foundry services. Use when creating new skills or updating existing skills.
Comprehensive map and workflows for the API domain. Triggers when users ask to 'design an API', 'secure the APIs', 'update endpoints', 'view the API ecosystem', or want to see all available API orchestration skills.
Execute Python code in isolated rootless containers with MCP server proxying for token-efficient agent workflows
Guides the agent through building LLM-powered applications with LangChain and stateful agent workflows with LangGraph. Triggered when the user asks to "create an AI agent", "build a LangChain chain", "create a LangGraph workflow", "implement tool calling", "build RAG pipeline", "create a multi-agent system", "define agent state", "add human-in-the-loop", "implement streaming", or mentions LangChain, LangGraph, chains, agents, tools, retrieval augmented generation, state graphs, or LLM orchestration.
Choose and combine Eve storage primitives to give agents persistent memory — short-term workspace, medium-term attachments and threads, long-term org docs and filesystem. Use when designing how agents remember, retrieve, and share knowledge.
Identifies and manages execution dependencies between agent skills by analyzing their inputs and outputs. Use when building multi-step agent workflows to ensure skills are executed in the correct order and that all required data is available.
Guidelines for creating well-structured AI agent skills. Use when building a new skill, reviewing skill quality, or unsure how to organize a skill.
Agent testing methodology - run agents with test inputs, observe outputs, iterate until outputs are accurate and well-structured.
Understand the components, mechanics, and constraints of context in agent systems. Use when writing, editing, or optimizing commands, skills, or sub-agents prompts.