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configure-dbt-source-freshness

configure-dbt-source-freshness is a skill for Claude Code from orchestra-hq/orchestra-skills. It costs 204 tokens per session (2,124 once invoked), scanned A, original, MIT.

A configuration tool for dbt source freshness, which checks how recently input data was loaded. It adds warning and error time limits and tells dbt where to find each source's load time.

In plain words
What is it for?
Use it to configure freshness in dbt source YAML for Snowflake, BigQuery, Databricks, or MotherDuck/DuckDB, then enable Orchestra state-aware orchestration. It writes configuration but does not run dbt or trigger pipelines.
Why use it?
It lets Orchestra identify stale or unchanged inputs and avoid running downstream models when their source data is not fresh.

Skill for Claude Code

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

Part of the orchestra plugin — 18 skills, 1 hook shipped together

not rated 9repo 3d ago A scan 204 tokens original MIT

Good fit Use it to configure freshness in dbt source YAML for Snowflake, BigQuery, Databricks, or MotherDuck/DuckDB, then enable Orchestra state-aware orchestration. It writes configuration but does not run dbt or trigger pipelines.

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Install with agentmods
npx agentmods add skills/orchestra-hq/orchestra-skills/configure-dbt-source-freshness
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 configure-dbt-source-freshness
Clone the repo
git clone --depth 1 https://github.com/orchestra-hq/orchestra-skills

Made for: Claude Code.

Or install orchestra, the plugin that ships this one along with the rest of its 18 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 configure-dbt-source-freshness

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/orchestra-hq/orchestra-skills/configure-dbt-source-freshness"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/configure-dbt-source-freshness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 204 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,124 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 $0.00204 $0.02124
Opus 5 $0.00102 $0.01062
Sonnet 5 $0.00041 $0.00425
Haiku 4.5 $0.00020 $0.00212

Measured 12d ago against content hash 00bcbaeb1a4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

configure-dbt-source-freshness 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 12d 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/orchestra/skills/configure-dbt-source-freshness/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Configure dbt source freshness

Author dbt source freshness so Orchestra can tell which sources have new data and skip downstream models when they don't. This is one half of state-aware orchestration (SAO); the other is build_after (see the configure-dbt-build-after skill). This skill writes config only — it does not run dbt or trigger pipelines. It explains how to verify instead.

When to use

  • User wants dbt source freshness configured, or stale-source detection.
  • User is setting up Orchestra state-aware orchestration and needs the freshness signal.
  • Files like models/staging/_sources.yml, sources.yml, or a dbt sources: block are in play.

What "done" looks like

  1. Freshness (warn_after/error_after, and an explicit loaded_at_field/loaded_at_query where the warehouse needs one) is added to the dbt sources YAML, correct for the warehouse.
  2. use_state_orchestration: true is set on the Orchestra dbt Core task (so the config is actually consumed). No dbt source freshness command is added to the pipeline — once SAO is on, Orchestra runs the freshness check itself. This skill only authors the config.
  3. A handoff explains what changed, the warehouse-specific choice made, how to verify, and any placeholders the user must fill.

Read first

Load these before editing — the warehouse file is the part most often wrong if guessed:

  • ../../references/orchestra/dbt-sao/source-freshness.md — freshness schema + the dbt-version placement trap (config: block in 1.9+, loaded_at_field in 1.10+).
  • ../../references/orchestra/dbt-sao/warehouses/<warehouse>.md — for the detected warehouse.
  • ../../references/orchestra/dbt-sao/orchestra-task.md — enabling SAO on the task.

Workflow

  1. Detect the warehouse. Read profiles.yml (the type: — snowflake, bigquery, databricks, duckdb/MotherDuck, redshift, fabric, postgres) or ask. The warehouse decides how freshness can be computed, and this is narrower than dbt's own metadata support — judge it by Orchestra SAO's matrix, not dbt's. Read the matching warehouses/*.md (other.md for anything unlisted).

Read the full file on GitHub · 124 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. 12d ago First seen · 124 lines · 204 tokens per session scan A 00bcbaeb1a4a

Subscribe to this mod's changes

configure-dbt-source-freshness is a skill published in the GitHub repository orchestra-hq/orchestra-skills (9 stars, last pushed 3d ago), licensed MIT. It adds 204 tokens to every session and 2,124 once invoked, about $0.0010 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 2026-08-31.

Analytics and metricsData and AI
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