- Exploring your agent’s surface area: see how it performs across normal cases and edge cases for every tool
- Regression testing: catch regressions in agent behavior and multi-turn tool use over time
- Improving your agent: generate fresh data for prompt optimization, fine-tuning, or regular development iteration
Agent simulation is currently in beta. To get access, email us at admin@guardrailsai.com and we’ll enable it for your account.
How it works at a high level
The flow for an agent simulation:- Register your tools with Snowglobe and instrument your code
- Start the
snowglobeprocess locally - Launch a simulation from the Snowglobe UI
- Snowglobe orchestrates persona-driven conversations with your agent
- When your agent calls a tool, Snowglobe can dynamically mock the response. No production data is touched
- Conversations and results appear as the simulation runs
Prerequisites
Before setting up agent simulation, you need:- A Snowglobe account: sign up or book a demo if you don’t have one
- Access to your agent’s source code: you’ll need to add a few lines of instrumentation
- A chatbot description: this tells Snowglobe what your agent does so it can generate relevant scenarios. See how to write a good chatbot description for guidance
- Snowglobe Connect SDK v0.6.0+: agent simulation requires the SDK. See the Snowglobe Connect overview if you haven’t set it up yet
Roadmap
Agent simulation is in active development. What’s coming:
Have a feature request? Email admin@guardrailsai.com. We’re shaping the roadmap based on beta feedback.
Concepts
Understand simulation modes and how tool mocking works under the hood.
Getting started
Set up your agent for agent simulation step by step.
Simulating widgets
Emit buttons, dropdowns, and forms from your agent and let Snowglobe simulate users interacting with them.