TinyTroupe is a Python library that uses large language models to simulate people with defined personalities, interests, and goals in artificial environments. It is used to explore human behavior, consumer types, and business scenarios through configurable multi-agent simulations. The catalogue entry provides an instruction for working with it.
Borrowing it
Nothing to install: this file belongs to microsoft/TinyTroupe. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/microsoft/TinyTroupe/main/.github/prompts/open-ended_ideas.prompt.mdgit clone --depth 1 https://github.com/microsoft/TinyTroupeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/microsoft/tinytroupe/open-ended_ideas)<a href="https://agentmods.dev/commands/microsoft/tinytroupe/open-ended_ideas"><img src="https://agentmods.dev/badge/commands/microsoft/tinytroupe/open-ended_ideas/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/microsoft/tinytroupe/open-ended_ideas"><img src="https://agentmods.dev/badge/commands/microsoft/tinytroupe/open-ended_ideas.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00008 | $0.00176 |
| Opus 5.5 | $0.00003 | $0.00070 |
| Sonnet 5.5 | $0.00002 | $0.00035 |
| Haiku 4.5 | $0.00001 | $0.00018 |
Grade A, and why
open-ended_ideas scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Examine the attached files in order to provide open-ended ideas for the project. They are not about programming specifically, but rather about the project itself, its goals, and how it can be improved or expanded.
Things to consider:
- Is the current state aligned with the project's goals?
- Are there clear opportunities for improvement or expansion?
- Could we have additional features very different from the current ones, but that complement them? For example, if the project only has a CLI interface, would it make sense to add a GUI interface?
- Are the abstractions and concepts used aligned with the domain or subject-matter of the project?
- Could we have additional abstractions or concepts that would expand or improve the domain or subject-matter coverage?
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 16 lines · 8 tokens per session scan A 000bf63c3ee5
open-ended_ideas is a command published in the GitHub repository microsoft/TinyTroupe (7,626 stars, last pushed 6d ago), licensed MIT. It adds 8 tokens to every session and 176 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-22.
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