> 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/fabricate/databases-and-data/simulations/simulation-run-workflow.md). # Running a simulation workflow Every simulation workflow shares the following parameters: * Run mode * Scenario * Database name * Model selection The workflow also includes simulation-specific parameters to adjust the time range and data volume for the prehistoric data and the simulation artifacts.

## Selecting the run mode From the **Run mode** dropdown list, select the run mode to use for the next run. ### Preview mode Preview mode provides a less expensive overview of the simulation results. It uses less expensive models, and does not generate any prehistoric data. Preview mode generates a limited number of records for each content platform. ### Complete mode Complete mode generates the complete timeline, prehistoric data, and simulation artifacts. ## Scenario The **Scenario** text area displays the full text of the scenario prompt. Before you run the simulation, you can make adjustments to the scenario. ## Database name In the **Database name** field, provide the name to use for the results entry in the [project navigation](/fabricate/projects/project-database-list.md). If you do not provide a name, then Fabricate sets the database name to the workflow name with the run date and time. For example: `Feature Planning Day Simulation 2026-10-01 15:20:09` ## Model selection For each simulation run, you can select the models to use to generate the timeline and to generate the prehistoric data and the simulation artifacts. --- # 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 by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.tonic.ai/fabricate/databases-and-data/simulations/simulation-run-workflow.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.