> For the complete documentation index, see [llms.txt](https://docs.tonic.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tonic.ai/app/structural-agent/agent-tasks-to-request.md). # What can you ask the Structural Agent to do? You can ask the Structural Agent to perform a variety of analysis and configuration tasks. The following are just a few examples.

Task	Example prompts
Navigate through the workspace	`Display Database View.` `Show me Table View for the transactions table.`
Ask questions about the workspace data	`How many name columns were detected in the data?` `Are there any sensitive columns in the customers table?` `Are there any JSON columns?`
Filter the workspace data columns	`Show me all of the unprotected datetime columns.` `Show me all of the primary key and foreign key columns.`
Set column sensitivity	`Make sure that all datetime columns are marked as sensitive.` `Mark the currently displayed columns as not sensitive.`
Ask for generator recommendations	`Suggest a generator for the occupation column.`
Configure column generators	`Apply the Timestamp Shift generator to all of the datetime columns. Shift the dates by 1 day before or after the current value.` `Apply the Custom Categorical generator to the product column. Generate 20 product names and enable consistency.` `Apply the Conditional generator to the seniority column. If the value of the column is less than 4, use the Random Integer generator to generate a replacement value between 0 and 4. If the value of the column is greater than or equal to 5, use the Random Integer generator to generate a value between 5 and 10.` `Apply the JSON Mask generator to the customer_summary column so that properties under name have the Name generator applied with the correct name type, the location properties have the Address generator applied with the correct location type, and the name property under work/properties has the Business Name generator applied.` `Apply the Regex Mask generator to the Product ID field to use the Random Integer generator to mask the numeric parts of the value.`
Display sample data	`Show me sample source and destination values for the last name column in the customers table.`
Manage subsetting	`Is subsetting enabled?` `How many tables are in the subset?` `How large will the subset be based on the current configuration?` `What is the subset target table configuration?` `Should any tables should be lookup tables?` `Enable setting and configure the transactions table as the target table. Use 5% of the records.` `Change the target table configuration to use records where the date is within the past 3 months.` `For the attendees table, filter optional records to include records where organization is test.` `Make vendor_type a lookup table.` `Enable subsetting and include tables that are not in the subset.`
Create and configure post-job scripts	`Create a post-job script to add demo users to the users table in the destination database.` `Enable the add demo users post-job script.` `Change the order of the post-job scripts to make the add demo users script run first.` `Delete the add demo users script.`
Identify and resolve schema changes	`Are there any schema changes that need to be resolved?` `Resolve the sensitive schema changes. Apply the Categorical generator to the new column.` `Dismiss the schema change notifications.`
Generate scripts and API calls Note that the Agent can only use the information available from this guide. It does not have access to the generated API reference.	`Can you show me the API call for assigning the Email generator to the email address columns?`

Note that Structural Agent requests are still subject to your global and workspace permissions. You cannot ask the Structural Agent to perform a task that you do not have permission to do. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## 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, and the optional `goal` query parameter: ``` GET https://docs.tonic.ai/app/structural-agent/agent-tasks-to-request.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.