What is dataproduct-implement?

A tool that turns an Entropy Data product's data contracts into dbt models and publishing files. dbt is a system for building data transformations from SQL in a repeatable pipeline.

Use it when an existing dbt project needs to implement a published Entropy Data product, including its input and output data structures.

It removes the manual work of translating a contract's schema into dbt project files. The contract remains the reference for what the pipeline should produce.

dataproduct-implement — Skill by entropy-data

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-implement

Any agent

npx skills add entropy-data/dataproduct-builder-dbt --skill dataproduct-implement

Clone the repo

git clone --depth 1 https://github.com/entropy-data/dataproduct-builder-dbt

Made for: Claude Code, Codex.

Per session 123 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,851 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.

Model	Per session	Once invoked
Fable 5	$0.00123	$0.04851
Opus 5	$0.00062	$0.02426
Sonnet 5	$0.00025	$0.00970
Haiku 4.5	$0.00012	$0.00485

Measured 2d ago against content hash 3bfcfd508c2e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

dataproduct-implement 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 2d 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-implement/SKILL.md · 238 lines

How it starts

The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implement a data product from its data contract

Turn an Entropy Data data product into a working dbt pipeline. The data contract (ODCS) is the source of truth for output schema; this skill reads it and writes the dbt artifacts that produce data matching the contract.

When to use this vs. other skills

Empty directory, no dbt project yet → run dataproduct-bootstrap first, then come back here.
Existing dbt project, need ODPS/ODCS/OpenLineage scaffolding only → use entropy-data-sync instead.
Existing dbt project, want to derive models from a published data contract → this skill.

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-implement. I'll:

Pre-checks: confirm this is a dbt project, the dbt CLI is installed, and the entropy-data CLI is connected.

Resolve the data product by id or URL (entropy-data dataproducts get).

Fetch each selected output port's data contract (entropy-data datacontracts get) and save it next to the SQL it governs, under models/output_ports/v<N>/.

Validate the contract against the target platform's conventions (e.g. UPPERCASE identifiers on Snowflake). If fixable bugs are found, offer to patch and publish the corrected contract back to Entropy Data.

Translate the ODCS schema into dbt models under models/output_ports/v1/ (column list, types, tests).

Implement the dbt model bodies: declare input ports as dbt sources, cache each upstream contract under models/input_ports/<provider-op-id>.odcs.yaml as a trust snapshot, and write the select from input ports to output columns (with confirmation; complex joins left as TODOs).

Stamp the data product on Entropy Data with the dataProductBuilder customProperty so the platform knows it is managed by this builder.

Hand off to entropy-data-sync to add any missing publishing artifacts (ODPS, OpenLineage, GitHub Actions).

Summarize what was generated and the open TODOs.

Read the full file on GitHub · 238 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.

2d ago First seen · 238 lines · 123 tokens per session scan A 3bfcfd508c2e

Subscribe to this mod's changes

dataproduct-implement is a skill published in the GitHub repository entropy-data/dataproduct-builder-dbt (12 stars, last pushed 3mo ago), licensed MIT. It adds 123 tokens to every session and 4,851 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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