> ## Documentation Index
> Fetch the complete documentation index at: https://docs.jedify.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Asker Examples

> Example prompts, and what your agent does with each.

You ask in plain language; your agent uses the Jedify tools to answer from your data. Three examples:

## See what you can ask

**Prompt:** "List 5 questions I can answer about our data with Jedify."

**Agent:** calls `contextualize` and `get_semantic_layer_entities` to read your semantic layer.

**Result:** concrete, answerable questions grounded in your data — not generic suggestions.

## Ask a direct question

**Prompt:** "What was total invoiced revenue in USD for the first half of 2026?"

**Agent:** calls `ask_a_single_question` — Jedify generates the query, runs it on your warehouse, and returns the data.

**Result:** the figure you asked for.

## Combine your data with the web

**Prompt:** "Pull our invoiced revenue by region for 2026, compare it to public industry growth rates, and write a short brief."

**Agent:** uses `ask_questions` for the internal numbers and its own web search for the benchmarks.

**Result:** a brief combining your figures with outside context. For deeper internal investigations ("why did X change?"), the agent uses `ask_a_research_question`.

## Tips

* Be specific with dates, metric names, and segments.
* Start with the headline number, then ask the agent to break it down.
* Say "research" or "investigate" to trigger a multi-step analysis.