# Context engine - [Context Graph](https://connectyai.gitbook.io/documentation/usage-guides/context-engine/context-graph.md) - [Overview](https://connectyai.gitbook.io/documentation/usage-guides/context-engine/overview.md) - [Catalog](https://connectyai.gitbook.io/documentation/usage-guides/context-engine/catalog.md) - [Metric Verse](https://connectyai.gitbook.io/documentation/usage-guides/context-engine/metric-verse.md) - [Day Zero Semantic Layer](https://connectyai.gitbook.io/documentation/usage-guides/context-engine/day-zero-semantic-layer.md): AI generated semantic layer on day zero, right after data source is connected - building the foundation of automated and trusted data governance. No manual modeling or Yaml/Json upload required. - [Data Quality](https://connectyai.gitbook.io/documentation/usage-guides/context-engine/data-quality.md): Connecty AI gives you data quality at every step of the pipeline with very granular control, so AI and users always see the most reliable input and output. - [Questions History](https://connectyai.gitbook.io/documentation/usage-guides/context-engine/questions-history.md): Track, filter, and explain every question and its metadata with full history details --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://connectyai.gitbook.io/documentation/usage-guides/context-engine.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.