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.

Then proceed.

Step 1 — Pre-checks

• Confirm the working directory is empty, or that it contains only files the user is fine with (e.g. an empty git repo, a LICENSE, or a README.md that will be overwritten).
• If dbt_project.yml already exists, stop and tell the user to use the entropy-data-sync skill instead. This skill is for greenfield only.
• Check whether the data product already exists in Entropy Data. Ask the user: "Is there already an ODPS draft for this data product in Entropy Data, or is it entirely new? If existing, paste the data product id or URL." Three outcomes:
  • New — continue to Step 2 with no DATA_PRODUCT preloaded.
  • Existing, id/URL given — extract the trailing id from a URL, then run entropy-data dataproducts get <id> -o yaml. If the lookup succeeds, remember the response as DATA_PRODUCT and use it in Step 2. If it returns a not-found error, tell the user and ask whether to (a) try a different id, (b) proceed as new with that id, or (c) abort.
  • Unsure — if the user does not know, default to asking for the id anyway and run the lookup. Do not silently assume "new".
• CLI prerequisites for the lookup (bootstrap is the one skill where this is global, not via the project venv — see AGENTS.md § Install pattern. The directory has no pyproject.toml yet, so uv run entropy-data is unavailable until Step 4 scaffolds the project and the user runs uv sync. Subsequent skills use uv run entropy-data exclusively.): entropy-data --version must be on PATH (install once with uv tool install entropy-data if missing) and entropy-data connection test must succeed. If either fails, surface the error and ask the user whether to (a) fix the CLI and retry, or (b) skip the lookup and proceed as if new. Don't prompt for the API key yourself; tell the user to run entropy-data connection add <name> --host <host> --api-key <key>.

Step 2 — Gather parameters

Set DBT_PROJECT_NAME = DATA_PRODUCT_ID once DATA_PRODUCT_ID is known.

Step 2a — If DATA_PRODUCT was loaded from Entropy Data

Derive parameters from the fetched ODPS. Treat the draft as authoritative; only ask the user for fields it does not specify.

Parameter	Source from DATA_PRODUCT
DATA_PRODUCT_ID	id
DATA_PRODUCT_NAME	name
PURPOSE	description.purpose (fall back to ask)
TEAM_NAME	team.name or team.id (fall back to ask, see picking note below)
PLATFORM	output port's server.type (fall back to ask)
CATALOG	output port's server.catalog / server.database / server.project (fall back to ask)
SCHEMA	output port's server.schema / server.dataset (fall back to ask)
TABLE	output port's server.table, or the linked contract's models: key (fall back to ask)

If the draft declares more than one output port, ask the user which one to use for PLATFORM/CATALOG/SCHEMA/TABLE. Default to the first.

Show the user the derived parameters and ask for confirmation before continuing. Collect any missing fields in one batched question.

Step 2b — If no draft was loaded (new product)

Ask the user for these in a single prompt. Do not generate any files until you have all of them.

Parameter	Description	Example
DATA_PRODUCT_ID	Stable id, snake_case, also the dbt project name	dp_acme_customer_activity
DATA_PRODUCT_NAME	Human-friendly name	Customer Activity
PURPOSE	One sentence — why this data product exists	Customer activity for customer success.
TEAM_NAME	Owning team	customer-success (see note below)
PLATFORM	databricks, snowflake, bigquery, or postgres	databricks
CATALOG (or equivalent)	Databricks catalog / Snowflake database / BigQuery project / Postgres database	entropy_data_prod
SCHEMA	Schema / dataset	dp_acme_customer_activity
TABLE	First output port table name	customer_activity

Picking TEAM_NAME: prefer a team id that already exists in Entropy Data so the data product slots into the team-scoped views in the UI. If the user does not already know the team id, invoke the entropy-data-teams skill (in this same plugin), let them pick, and use the returned id as TEAM_NAME. A free-text value is still accepted (the ODPS schema does not enforce membership), but the registered id is preferred.

Step 3 — Pick the dbt adapter and profile block

Map PLATFORM to the right dbt adapter package and the profiles.yml.example body:

PLATFORM	DBT_ADAPTER	PROFILE_BLOCK (substituted into profiles.yml.example)
databricks	dbt-databricks	type: databricks catalog: <CATALOG> schema: <SCHEMA> host: <fill in> http_path: <fill in> token: <fill in> threads: 4
snowflake	dbt-snowflake	type: snowflake account: <fill in> user: <fill in> password: <fill in> role: <fill in> database: <CATALOG> warehouse: <fill in> schema: <SCHEMA> threads: 4
bigquery	dbt-bigquery	type: bigquery method: oauth project: <CATALOG> dataset: <SCHEMA> location: <fill in> threads: 4
postgres	dbt-postgres	type: postgres host: <fill in> user: <fill in> password: <fill in> port: 5432 dbname: <CATALOG> schema: <SCHEMA> threads: 4

Step 4 — Scaffold the dbt project

Templates are at ${PLUGIN_ROOT}/skills/dataproduct-bootstrap/templates/. Copy each template into the working directory, substituting placeholders.

Template	Destination
pyproject.toml	pyproject.toml (substitute {{DBT_ADAPTER}} — dbt-snowflake, dbt-databricks, etc. — so uv sync installs the right adapter alongside the other dev deps)
dbt_project.yml	dbt_project.yml
.gitignore	.gitignore (merge if one already exists; do not overwrite)
README.md	README.md (merge or back up if one already exists)
profiles.yml.example	profiles.yml.example
models/input_ports/_models.yml	models/input_ports/_models.yml
models/staging/_models.yml	models/staging/_models.yml
models/intermediate/_models.yml	models/intermediate/_models.yml
models/output_ports/v1/_models.yml	models/output_ports/v1/_models.yml

Also create empty directories analyses/, macros/, seeds/, snapshots/, tests/. If a directory cannot be empty in git, drop a single .gitkeep file.

Check the user's existing ~/.dbt/profiles.yml

After scaffolding, run a read-only check against ~/.dbt/profiles.yml (it likely already exists if the user works on other dbt projects). Do not modify it. Record one of three outcomes — Step 6 uses this to pick the right next-steps bullet and table entry.

• missing — file does not exist. User can copy profiles.yml.example as-is.
• exists, no collision — file exists but does not define a top-level key <DBT_PROJECT_NAME>:. User must merge the new profile block into it.
• exists, collision — file exists and already defines <DBT_PROJECT_NAME>:. Flag prominently; user must reconcile (rename this project, replace the existing block, or confirm it already points at the right warehouse).

Check with test -f ~/.dbt/profiles.yml for existence and grep -nE '^<DBT_PROJECT_NAME>:' ~/.dbt/profiles.yml for the collision. Top-level YAML keys only — do not match nested occurrences.

Step 5 — Hand off to entropy-data-sync

Now the dbt skeleton is in place. Invoke the entropy-data-sync skill (in this same plugin) to add ODPS, ODCS, OpenLineage transport, and the GitHub Actions workflow.

Pass the parameters you already collected (DATA_PRODUCT_ID, DATA_PRODUCT_NAME, PURPOSE, TEAM_NAME, PLATFORM, CATALOG, SCHEMA, TABLE) so the user does not have to answer them again. entropy-data-sync resolves API_HOST itself from the entropy-data CLI connection.

If DATA_PRODUCT was loaded from Entropy Data in Step 1, do this before invoking entropy-data-sync so its audit sees the artifacts as already present (no template-generated stubs that would clobber the draft):

1. Write the fetched ODPS to <DATA_PRODUCT_ID>.odps.yaml (the same YAML the CLI returned — do not regenerate from the template).
2. For each output port in the draft that references a contract id, fetch and save it: entropy-data datacontracts get <contract-id> -o yaml > models/output_ports/v<N>/<contract-id>.odcs.yaml (default v1 if the output port does not declare a version).
3. If any of these fetches fail (404, network error), surface the error and continue — entropy-data-sync will create stubs from templates for whatever is missing.

The integration skill will run its own audit. For a brand-new product, every artifact is missing and created; for a draft-loaded product, ODPS and ODCS show as already present and sync just fills in OpenLineage, the workflow, and the model-layout placeholders.

Step 6 — Final report

After both skills have run, end with this two-part recap. Use the same Status enum the other skills use: created, updated, already present, deferred, skipped.

Part 1 — outcome table. State the mode at the top of the recap — one of Mode: new product or Mode: bootstrapped from existing draft <DATA_PRODUCT_ID>.

Artifact	Status	Details
dbt_project.yml	…	adapter = <DBT_ADAPTER>, models block configured
profiles.yml.example	…	platform = <PLATFORM>
README.md	…	new or merged into existing
.gitignore	…	new or merged into existing
Model layout	…	models/{input_ports,staging,intermediate,output_ports/v1}/ + _models.yml placeholders
Empty dbt dirs	…	analyses/, macros/, seeds/, snapshots/, tests/
<DATA_PRODUCT_ID>.odps.yaml (from draft)	…	only when bootstrapped from existing draft: created (fetched) or skipped (fetch failed)
Output-port ODCS files (from draft)	…	only when bootstrapped from existing draft: <N> file(s) under models/output_ports/v<N>/, or skipped if no contracts were linked
~/.dbt/profiles.yml (local)	deferred	one of: missing, exists – merge required, or collision: <DBT_PROJECT_NAME> already defined
entropy-data-sync handoff	…	"ran" / "skipped" — see sync's own report for ODPS/ODCS/OpenLineage/workflow rows

Part 2 — next steps. Bullet list, include only what applies:

• uv venv && source .venv/bin/activate && uv pip install dbt-core <DBT_ADAPTER> openlineage-dbt datacontract-cli entropy-data
• Wire up ~/.dbt/profiles.yml (pick the bullet that matches the Step 4 check):
  • missing → cp profiles.yml.example ~/.dbt/profiles.yml, then fill in credentials.
  • exists, no collision → append the <DBT_PROJECT_NAME>: block from profiles.yml.example to ~/.dbt/profiles.yml, then fill in credentials.
  • exists, collision → <DBT_PROJECT_NAME>: is already defined in ~/.dbt/profiles.yml. Reconcile manually: rename this project, replace the existing block, or confirm it already points at the right warehouse.
• git init && git add . && git commit -m "Initial commit" (if the directory is not already a git repo).
• Create a GitHub repo and push; set the secrets called out by the sync skill (ENTROPY_DATA_API_KEY, platform creds).
• Fill in the data contract schema in models/output_ports/v1/<CONTRACT_FILE>.
• Any deferred items surfaced by the sync skill's report (e.g. git connections to register after first CI publish).

If there is nothing in Part 2, write a single line: No further action required.

Constraints

• Do not run dbt init — it generates an example layout that does not match the Entropy Data conventions. Use the templates here.
• Do not commit secrets. profiles.yml is in .gitignore; only profiles.yml.example is checked in.
• Do not invent credentials. Every secret in profiles.yml.example should be a <fill in> placeholder.
• Idempotent on greenfield only. If dbt_project.yml exists, route the user to entropy-data-sync; do not overwrite.
• Do not run git init, git commit, or any push — surface those as next steps for the user instead.