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Found 32 Skills
Install and configure ktx, the self-improving context layer that teaches AI agents to query data warehouses accurately with approved metrics, semantic layer, and business knowledge.
Bootstrap a nao agent for a project — gather warehouse + scope + extra-context info in one round, look up the warehouse-specific config from nao docs, write nao_config.yaml, run nao init + nao sync, set up the LLM key, and generate the first RULES.md. Use when the user has just decided to use nao on a new project. Only for first-time setup; for editing rules, generating tests, or reviewing an existing context, use write-context-rules / create-context-tests / audit-context.
Expert in using ktx, the executable context layer for data and analytics agents that enables accurate querying through MCP with skills, memory and a semantic layer
Configure and use ktx to build an executable context layer for AI agents querying data warehouses with semantic layers, wiki knowledge, and approved metrics
Context layer for AI data agents - query warehouses accurately with semantic layers, metrics, and wiki knowledge through MCP
Context layer for data agents - builds semantic layer, wiki, and warehouse metadata to enable accurate AI-powered analytics queries
Context layer for data and analytics AI agents with semantic layer, skills, and memory via MCP
Use ktx to build a self-improving context layer that teaches AI agents how to query data warehouses accurately with approved metrics, semantic layers, and business knowledge