# Simulate buyer and user personas to pressure-test ideas and messaging with TinyTroupe

> Use TinyTroupe when an agent should run simulated persona panels, synthetic interviews, or offline audience reactions before spending on campaigns, launches, or user research.

- Skill: `agentskillexchange/simulate-buyer-and-user-personas-to-pressure-test-ideas-and-` (Agent Skill)
- Install (CLI): `npx skillmds@latest add agentskillexchange/simulate-buyer-and-user-personas-to-pressure-test-ideas-and-`
- Raw SKILL.md: https://api.skillmd.com/api/skills/agentskillexchange/simulate-buyer-and-user-personas-to-pressure-test-ideas-and-/raw
- Safety review: pending (external: skill-scanner PASS, skillspector CAUTION)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: agentskillexchange (https://skillmd.com/u/agentskillexchange)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/agentskillexchange/simulate-buyer-and-user-personas-to-pressure-test-ideas-and-

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# Simulate buyer and user personas to pressure-test ideas and messaging with TinyTroupe

Use TinyTroupe when an agent should run simulated persona panels, synthetic interviews, or offline audience reactions before spending on campaigns, launches, or user research.

## Prerequisites

Python, pip, access to a supported LLM provider

## Installation

Use the upstream install or setup path that matches your environment:
- conda create -n tinytroupe python=3.10
- conda activate tinytroupe
- Use pip to install the library **directly from this repository** (we **will not install from PyPI**):
- pip install git+https://github.com/microsoft/TinyTroupe.git@main

Requirements and caveats from upstream:
- *TinyTroupe* is an experimental Python library that allows the **simulation** of people with specific personalities, interests, and goals. These artificial agents - TinyPersons - can listen to us and one another, repl...
- Internal LLM usage is now better supported via the LLMChat class, and also the @llm decorator, which transform any standard Python function into an LLM-based one (i.e., by using the docstring as part of the prompt, an...
- Python 3.10 or higher. We'll assume you are using [Anaconda](https://docs.anaconda.com/anaconda/install/), but you can use other Python distributions.

Basic usage or getting-started notes:
- Take a look one example [Vision for Product, Diagnosis and Appreciation Feedback (image modality)](./examples/Vision%20for%20Product%2C%20Diagnosis%20and%20Appreciation%20Feedback%20%28image%20modality%29.ipynb) noteb...
- New example notebooks demonstrating empirical validation against real survey data.
- TinyWorld now run agents in parallel within each simulation step, allowing faster simulations.

- Source: https://github.com/microsoft/TinyTroupe
- Extracted from upstream docs: https://raw.githubusercontent.com/microsoft/TinyTroupe/HEAD/README.md

## Documentation

- https://github.com/microsoft/TinyTroupe#readme

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/simulate-buyer-and-user-personas-to-pressure-test-ideas-and-messaging-with-tinytroupe/)