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dataproduct-exampledata

dataproduct-exampledata is a skill for Claude Code, Codex from entropy-data/dataproduct-builder-dbt. It costs 83 tokens per session (2,026 once invoked), scanned A, original, MIT.

A workflow for publishing a small, scrubbed sample of data from a dbt output. dbt is a tool for building data transformations, and PII means information that can identify a person.

In plain words
What is it for?
Checking contracts and non-production settings, removing or transforming sensitive fields, extracting sample rows, preparing the upload file, and sending it through the Entropy Data command-line tool.
Why use it?
It lets potential data users inspect example rows while reducing exposure of private or sensitive information and avoiding production data.

Skill for Claude CodeCodex

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the dataproduct-builder-dbt plugin — 8 skills, 1 hook shipped together

not rated 12 3mo ago A scan 83 tokens original MIT
View the source file entropy-data/dataproduct-builder-dbt
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/entropy-data/dataproduct-builder-dbt/dataproduct-exampledata
Any agent
npx skills add entropy-data/dataproduct-builder-dbt --skill dataproduct-exampledata
Clone the repo
git clone --depth 1 https://github.com/entropy-data/dataproduct-builder-dbt

Made for: Claude Code, Codex.

Or install dataproduct-builder-dbt, the plugin that ships this one along with the rest of its 8 skills, 1 hook.

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.

agentmods badge for dataproduct-exampledata

README.md
[![agentmods](https://agentmods.dev/badge/skills/entropy-data/dataproduct-builder-dbt/dataproduct-exampledata.svg)](https://agentmods.dev/skills/entropy-data/dataproduct-builder-dbt/dataproduct-exampledata)
Your own site
<a href="https://agentmods.dev/skills/entropy-data/dataproduct-builder-dbt/dataproduct-exampledata"><img src="https://agentmods.dev/badge/skills/entropy-data/dataproduct-builder-dbt/dataproduct-exampledata.svg" alt="Measured on agentmods" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,026 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00083 $0.02026
Opus 5 $0.00042 $0.01013
Sonnet 5 $0.00017 $0.00405
Haiku 4.5 $0.00008 $0.00203

Measured 5d ago against content hash 49fcd082a75a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

dataproduct-exampledata 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 5d 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.

skills/dataproduct-exampledata/SKILL.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Upload example data for a data product

Sample rows let prospective consumers evaluate a data product without requesting access. This skill pulls a small sample from a non-production source, scrubs sensitive columns, and uploads the result.

How to run this skill

${PLUGIN_ROOT} below refers to the root of this plugin — the directory that contains skills/. On Claude Code it is set automatically as ${CLAUDE_PLUGIN_ROOT} — use that. On any other agent (Codex, Copilot CLI, etc.) it is unset; resolve it as ../.. relative to this SKILL.md file's directory (i.e. the grandparent of skills/<this-skill>/).

Plan announcement (before Step 0)

Before running Step 0, print this plan to the user verbatim:

Running dataproduct-exampledata. I'll:

  1. Pre-checks: dbt project, ODCS files, entropy-data CLI, non-prod dbt target.
  2. Identify the output port and its contract.
  3. Build a scrub plan — drop PII/sensitive columns, hash IDs, drop free text. Wait for your confirmation.
  4. Extract ~20 sample rows via dbt show against the non-prod target.
  5. Build the example-data YAML and show the first rows. Wait for your confirmation.
  6. Upload via entropy-data example-data put.
  7. Summarize what was uploaded, what was scrubbed, and cleanup options.

Then proceed.

Step 0 — Pre-checks

  • Confirm dbt_project.yml exists at the working directory root.
  • Confirm there is at least one output-port ODCS file under models/output_ports/.
  • Confirm uv run --quiet entropy-data --version succeeds from the project root. If it fails, run uv sync and retry; if still missing, stop and tell the user to verify entropy-data is listed in pyproject.toml's [dependency-groups].dev. Use uv run entropy-data … for every CLI invocation in this skill.
  • Confirm a non-production dbt profile/target exists (test, dev, or similar). Inspect profiles.yml if accessible; otherwise ask. Never use a prod target in this skill.

Step 1 — Identify the output port

Read the full file on GitHub · 141 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.

  1. 5d ago First seen · 141 lines · 83 tokens per session scan A 49fcd082a75a

Subscribe to this mod's changes

dataproduct-exampledata is a skill published in the GitHub repository entropy-data/dataproduct-builder-dbt (12 stars, last pushed 3mo ago), licensed MIT. It adds 83 tokens to every session and 2,026 once invoked, about $0.0004 per session on Opus 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.

Data and AIdataproduct-builder
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