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dbt-core-prefect-to-orchestra

dbt-core-prefect-to-orchestra is a skill for Claude Code from orchestra-hq/orchestra-skills. It costs 103 tokens per session (2,381 once invoked), scanned A, original, MIT.

A conversion guide for moving Prefect tasks that run dbt, a tool for building and testing data transformations, into Orchestra pipeline tasks. It covers dbt Core commands and dbt Cloud jobs.

In plain words
What is it for?
Rewriting dbt Core or dbt Cloud tasks from Prefect as Orchestra pipeline YAML, including command lists, package managers, and connection details.
Why use it?
It maps Prefect settings to Orchestra fields so the migration does not require guessing how commands, Python versions, package managers, or connections correspond.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the migrate-to-orchestra plugin — 52 skills shipped together

not rated 9repo changed 8d ago A scan 103 tokens original MIT

Good fit Rewriting dbt Core or dbt Cloud tasks from Prefect as Orchestra pipeline YAML, including command lists, package managers, and connection details.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/orchestra-hq/orchestra-skills/dbt-core-prefect-to-orchestra
View source ↗ orchestra-hq/orchestra-skills
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.

Any agent
npx skills add orchestra-hq/orchestra-skills --skill dbt-core-prefect-to-orchestra
Clone the repo
git clone --depth 1 https://github.com/orchestra-hq/orchestra-skills

Made for: Claude Code.

Or install migrate-to-orchestra, the plugin that ships this one along with the rest of its 52 skills.

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 dbt-core-prefect-to-orchestra

README.md
[![agentmods](https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/dbt-core-prefect-to-orchestra/github.svg)](https://agentmods.dev/skills/orchestra-hq/orchestra-skills/dbt-core-prefect-to-orchestra)
Your own site
<a href="https://agentmods.dev/skills/orchestra-hq/orchestra-skills/dbt-core-prefect-to-orchestra"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/dbt-core-prefect-to-orchestra/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.

agentmods 80×15 button for dbt-core-prefect-to-orchestra

Your own site · 80×15
<a href="https://agentmods.dev/skills/orchestra-hq/orchestra-skills/dbt-core-prefect-to-orchestra"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/dbt-core-prefect-to-orchestra.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 103 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,381 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00103 $0.02381
Opus 5.5 $0.00041 $0.00952
Sonnet 5.5 $0.00021 $0.00476
Haiku 4.5 $0.00010 $0.00238

Measured 8d ago against content hash dc7c153caa5f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

dbt-core-prefect-to-orchestra 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 8d 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/migrate-to-orchestra/skills/dbt-core-prefect-to-orchestra/SKILL.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

Converts Prefect dbt tasks into Orchestra pipeline YAML. Two dbt variants exist:

  • dbt Core (DbtCoreOperation, ShellOperation running dbt CLI): integration: DBT_CORE, integration_job: DBT_CORE_EXECUTE
  • dbt Cloud (DbtCloudJob): integration: DBT, integration_job: DBT_RUNJOB

The commands list from Prefect is joined into a single semicolon-delimited string. Warehouse credentials and Git repo details go on the Orchestra dbt Core connection, not in YAML.

Parameter Mapping

Prefect construct Orchestra field Notes
DbtCoreOperation(commands=[...]) parameters.commands Join list items with ; — e.g. 'dbt seed; dbt build;'
Python version parameters.python_version '3.11', '3.12', '3.13' or '3.14' — defaults to '3.12'. Carry the source project's version over when it's one of these; if it pins something older or newer, flag it rather than silently downgrading
pip / poetry / uv parameters.package_manager PIP, POETRY, or UV — infer from visible project files (poetry.lock/pyproject.toml → POETRY, uv.lock → UV, requirements.txt/Pipfile → PIP). If none of that is visible, don't silently guess PIP — see Gotchas
Git repo + profiles.yml / warehouse creds connection: Set up in Connectors → dbt Core
--select, --exclude, --target flags inline in parameters.commands e.g. dbt build --select tag:daily --target prod;
project_dir parameters.project_dir A real task parameter — the subdirectory holding dbt_project.yml. Carry the value over; null if the project is at the repo root
DbtCloudJob(job_id=..., account_id=...) integration: DBT, integration_job: DBT_RUNJOB, parameters.job_id account_id goes on the Orchestra dbt Cloud connection
ShellOperation(commands=["dbt build"]) same as DbtCoreOperation Treat identically

Orchestra YAML Structure

dbt Core:

version: v1
name: dbt-flow
pipeline:
  stage-001:
    tasks:
      task-001:
        integration: DBT_CORE
        integration_job: DBT_CORE_EXECUTE
        name: dbt_daily_build
        connection: data_dbt_bigquery_prod_12345
        parameters:
          commands: 'dbt seed; dbt build --select tag:daily --target prod;'
          package_manager: PIP
          python_version: '3.12'
          project_dir: null   # optional — subdirectory holding dbt_project.yml, e.g. 'dbt' in a monorepo
        depends_on: []
        condition: null
        tags: []

Read the full file on GitHub · 172 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. 8d ago Changed dc7c153caa5f
  2. 9d ago Changed 577c316a3f52
  3. 25d ago Changed · +24 lines 7e5c26d52e51
  4. 2mo ago First seen · 148 lines · 103 tokens per session scan A ac545a524f17

Subscribe to this mod's changes

dbt-core-prefect-to-orchestra is a skill published in the GitHub repository orchestra-hq/orchestra-skills (9 stars, last pushed yesterday), licensed MIT. It adds 103 tokens to every session and 2,381 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-31.

Data and AIDevOps and cloud
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