NVIDIA-NeMo/DataDesigner is a framework for generating synthetic datasets from scratch or from seed data, including text, structured records and images, while controlling field relationships and validating results. Data scientists and developers use it to create and evaluate data-generation workflows that can include models, seed datasets, external tools and custom validators. The catalogue entries provide agent skills, agents, instructions and settings for working with Data Designer.
Borrowing it
Nothing to install: this file belongs to NVIDIA-NeMo/DataDesigner. 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/NVIDIA-NeMo/DataDesigner/main/AGENTS.mdgit clone --depth 1 https://github.com/NVIDIA-NeMo/DataDesignerWrote 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/instructions/nvidia-nemo/datadesigner/agents-md)<a href="https://agentmods.dev/instructions/nvidia-nemo/datadesigner/agents-md"><img src="https://agentmods.dev/badge/instructions/nvidia-nemo/datadesigner/agents-md/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/instructions/nvidia-nemo/datadesigner/agents-md"><img src="https://agentmods.dev/badge/instructions/nvidia-nemo/datadesigner/agents-md.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 | $0.00922 | $0.00922 |
| Opus 5.5 | $0.00369 | $0.00369 |
| Sonnet 5.5 | $0.00184 | $0.00184 |
| Haiku 4.5 | $0.00092 | $0.00092 |
Grade A, and why
DataDesigner AGENTS.md 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file is for agents developing DataDesigner — the codebase you are working in.
If you are an agent helping a user build a dataset, use the data-designer skill and the product documentation instead.
DataDesigner is an NVIDIA NeMo framework for creating synthetic datasets from scratch. Users declare what their data should look like (columns, types, relationships, validation rules); the engine figures out how to generate it. Every change you make should preserve this "declare, don't orchestrate" contract.
The Layering Is Structural
The data_designer namespace is split across three installable packages that merge at runtime via PEP 420 implicit namespace packages (no top-level __init__.py).
| Package | Path | Owns |
|---|---|---|
data-designer-config |
packages/data-designer-config/ |
data_designer.config — column configs, model configs, sampler params, builder API, plugin system, lazy imports |
data-designer-engine |
packages/data-designer-engine/ |
data_designer.engine — column generators, dataset builders, DAG execution, model facade, validators, sampling |
data-designer |
packages/data-designer/ |
data_designer.interface — public DataDesigner class, results, errors; data_designer.cli — CLI entry point; data_designer.integrations |
Dependency direction (left depends on right): interface → engine → config. Never import against this flow.
Core Concepts
- Column — a named field in the output dataset, defined by a column config
- Sampler — a built-in statistical generator (UUID, Category, Uniform, Gaussian, Person, DateTime, etc.)
- Seed dataset — an existing dataset used as input for generation
- Processor — a post-generation transformation applied to column values
- Model — an LLM endpoint configured via
ModelConfigand accessed through the model facade - Plugin — a user-supplied extension registered via entry points (custom column generators, validators, profilers)
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.
- 1mo ago Changed · +1 lines · +16 tokens per session 33510470e4b8
- 1mo ago First seen · 57 lines · 906 tokens per session scan A b423835c10e7
DataDesigner AGENTS.md is an instructions file published in the GitHub repository NVIDIA-NeMo/DataDesigner (2,366 stars, last pushed today), licensed Apache-2.0. It adds 922 tokens to every session, about $0.0037 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 2026-08-30.
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