A command workflow for creating or updating realistic sample data for a product screen, along with matching TypeScript types. It first uses the product roadmap and section specification to identify what the data should contain.

Generating section data, updating its TypeScript type definitions, and preparing realistic content for screen designs.

It prevents sample data from being created without a defined screen or data structure. It also accounts for existing data so current work is not changed without checking what needs updating.

How buildermethods/design-os configures Claude Code

About the project

Design OS is a product-planning and interface-design tool that guides an idea through product definition, data modeling, design-system choices, screen design, and implementation handoff. Teams use it to give coding agents a clear specification before development begins. Its catalogue add-ons support the guided planning and design workflow.

buildermethods/design-os · 1,876 stars · on GitHub

Reuse

Borrowing it

Nothing to install: this file belongs to buildermethods/design-os. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/buildermethods/design-os/main/.claude/commands/design-os/sample-data.md

Clone the repo

git clone --depth 1 https://github.com/buildermethods/design-os

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/buildermethods/design-os/sample-data/github.svg)](https://agentmods.dev/commands/buildermethods/design-os/sample-data)

Your own site

<a href="https://agentmods.dev/commands/buildermethods/design-os/sample-data"><img src="https://agentmods.dev/badge/commands/buildermethods/design-os/sample-data/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/buildermethods/design-os/sample-data"><img src="https://agentmods.dev/badge/commands/buildermethods/design-os/sample-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 2,006 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00000	$0.02006
Opus 5.5	$0.00000	$0.00802
Sonnet 5.5	$0.00000	$0.00401
Haiku 4.5	$0.00000	$0.00201

Measured 2mo ago against content hash 2d7592b5f783, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

sample-data 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 2mo 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.

.claude/commands/design-os/sample-data.md · 234 lines

How it starts

The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Sample Data

You are helping the user create or update realistic sample data for a section of their product. This data will be used to populate screen designs. You will also generate TypeScript types based on the data structure.

Step 1: Check Prerequisites

First, identify the target section and verify that spec.md exists for it.

Read /product/product-roadmap.md to get the list of available sections.

If there's only one section, auto-select it. If there are multiple sections, use the AskUserQuestion tool to ask which section the user wants to generate data for.

Then check if product/sections/[section-id]/spec.md exists. If it doesn't:

"I don't see a specification for [Section Title] yet. Please run /shape-section first to define the section's requirements, then come back to generate sample data."

Stop here if the spec doesn't exist.

Step 2: Check for Existing Sample Data

Check if product/sections/[section-id]/data.json already exists.

If sample data already exists:

Read the existing data.json and types.ts files, then ask the user:

"Sample data already exists for [Section Title]. What would you like to change about the existing data shape or sample data?"

Wait for the user's response describing what they want changed. Once you receive their notes, immediately proceed to update data.json and types.ts based on their requested changes — do not present a draft for approval.

After updating, inform the user:

"I've updated the sample data and types for [Section Title] based on your feedback. Review the changes and let me know if you'd like further adjustments, or run /design-screen when you're ready."

Stop here — the remaining steps below are for generating new data from scratch.

If no sample data exists: Continue to Step 3.

Step 3: Check for Global Data Shape

Check if /product/data-shape/data-shape.md exists.

If it exists:

Read the file to understand the global entity definitions
Entity names in your sample data should match the global data shape
Use the descriptions and relationships as a guide

Read the full file on GitHub · 234 lines

Changes

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.

2mo ago First seen · 234 lines · 0 tokens per session scan A 2d7592b5f783

Subscribe to this mod's changes

sample-data is a command published in the GitHub repository buildermethods/design-os (1,876 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,006 tokens. 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.

Frontend

sample-data next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
sample-databuildermethods/design-os	Command	1.9k	1mo ago	MIT	A	0	Claude Code
checklistgithub/spec-kit	Command	148k	yesterday	MIT	A	13	Claude Code
clarifygithub/spec-kit	Command	148k	yesterday	MIT	A	27	Claude Code
specifygithub/spec-kit	Command	148k	yesterday	MIT	A	13	Claude Code
convergegithub/spec-kit	Command	148k	yesterday	MIT	A	35	Claude Code
implementgithub/spec-kit	Command	148k	yesterday	MIT	A	14	Claude Code
speckit.bug.fixgithub/spec-kit	Command	148k	yesterday	MIT	A	12	Claude Code

design-os: Command for Claude Code