dataproduct-bootstrap

A setup workflow for creating a new Entropy Data dbt project from an empty directory. It creates the standard project files, model folders, example warehouse settings, data contracts, and related pipeline configuration.

In plain words
What is it for?
Use it to start a new dbt data product project and prepare its input, staging, intermediate, and versioned output model structure.
Why use it?
It removes the repetitive initial setup needed before building a data product. It also establishes the project's expected layout and handoff to data synchronization.

Skill for Claude CodeCodex

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

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-bootstrap
Any agent
npx skills add entropy-data/dataproduct-builder-dbt --skill dataproduct-bootstrap
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.

Per session 121 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,059 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 $0.00121 $0.04059
Opus 5 $0.00060 $0.02030
Sonnet 5 $0.00024 $0.00812
Haiku 4.5 $0.00012 $0.00406

Measured 3d ago against content hash aeb9e8699b8b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

dataproduct-bootstrap 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 3d 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-bootstrap/SKILL.md · 196 lines

How it starts

The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Bootstrap a new dbt data product

Create a new dbt data product project that follows the Entropy Data conventions. This skill handles the greenfield case — empty directory, no dbt project yet. For an existing dbt project that just needs the Entropy Data layer, use the entropy-data-sync skill instead.

What this skill produces

After running, the directory contains:

.
├── dbt_project.yml
├── pyproject.toml
├── .gitignore
├── README.md
├── profiles.yml.example
├── models/
│   ├── input_ports/_models.yml
│   ├── staging/_models.yml
│   ├── intermediate/_models.yml
│   └── output_ports/v1/_models.yml
├── analyses/      # empty
├── macros/        # empty
├── seeds/         # empty
├── snapshots/     # empty
└── tests/         # empty

It then invokes entropy-data-sync to add <id>.odps.yaml, the output-port contract under models/output_ports/v1/<contract>.odcs.yaml, openlineage.yml, and .github/workflows/data-product.yml.

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 1)

Before running Step 1, print this plan to the user verbatim:

Running dataproduct-bootstrap. I'll:

  1. Pre-checks: confirm the working directory is empty (greenfield only), then ask whether this is a brand-new data product or one that already has an ODPS draft in Entropy Data.
  2. Gather parameters. If you point me at an existing draft, I pull them from the fetched ODPS; otherwise I'll ask you in one batched question (data product id, team, platform, catalog/schema, table).
  3. Pick the dbt adapter and profile block for the chosen platform.
  4. Scaffold the dbt project (dbt_project.yml, profiles.yml.example, model layout, README, .gitignore), and check whether the user's existing ~/.dbt/profiles.yml would collide with the new profile.
  5. Hand off to entropy-data-sync for the publishing layer (ODPS, ODCS, OpenLineage, GitHub Actions).
  6. Summarize what was scaffolded and the next manual steps.

Read the full file on GitHub · 196 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. 3d ago First seen · 196 lines · 121 tokens per session scan A aeb9e8699b8b

Subscribe to this mod's changes

dataproduct-bootstrap is a skill published in the GitHub repository entropy-data/dataproduct-builder-dbt (12 stars, last pushed 3mo ago), licensed MIT. It adds 121 tokens to every session and 4,059 once invoked, about $0.0006 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.

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