maintaining-dbt-documentation

maintaining-dbt-documentation is a skill for Claude Code from dbt-labs/dbt-agent-skills. It costs 77 tokens per session (1,877 once invoked), scanned A, original, Apache-2.0.

A workflow for auditing and filling gaps in dbt documentation. It checks model and column descriptions in YAML files, where dbt stores metadata alongside SQL models.

In plain words
What is it for?
Use it to find undocumented models or columns, draft descriptions in the project's existing writing style, and recheck documentation coverage.
Why use it?
It helps keep documentation complete and consistent as models change, while leaving proposed edits for a person to review.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the dbt plugin — 11 skills shipped together

Good fit Use it to find undocumented models or columns, draft descriptions in the project's existing writing style, and recheck documentation coverage.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dbt-labs/dbt-agent-skills/maintaining-dbt-documentation
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 dbt-labs/dbt-agent-skills --skill maintaining-dbt-documentation
Clone the repo
git clone --depth 1 https://github.com/dbt-labs/dbt-agent-skills

Made for: Claude Code.

Or install dbt, the plugin that ships this one along with the rest of its 11 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 maintaining-dbt-documentation

README.md
[![agentmods](https://agentmods.dev/badge/skills/dbt-labs/dbt-agent-skills/maintaining-dbt-documentation/github.svg)](https://agentmods.dev/skills/dbt-labs/dbt-agent-skills/maintaining-dbt-documentation)
Your own site
<a href="https://agentmods.dev/skills/dbt-labs/dbt-agent-skills/maintaining-dbt-documentation"><img src="https://agentmods.dev/badge/skills/dbt-labs/dbt-agent-skills/maintaining-dbt-documentation/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 maintaining-dbt-documentation

Your own site · 80×15
<a href="https://agentmods.dev/skills/dbt-labs/dbt-agent-skills/maintaining-dbt-documentation"><img src="https://agentmods.dev/badge/skills/dbt-labs/dbt-agent-skills/maintaining-dbt-documentation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,877 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00077 $0.01877
Opus 5 $0.00039 $0.00938
Sonnet 5 $0.00015 $0.00375
Haiku 4.5 $0.00008 $0.00188

Measured 11d ago against content hash 61359d2f9fec, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

maintaining-dbt-documentation 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 11d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (audit_coverage.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/dbt/skills/maintaining-dbt-documentation/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Maintaining dbt Documentation

Keep a dbt project's model and column documentation complete and consistent as it grows. This skill (1) audits which models lack YAML documentation, (2) drafts the missing descriptions in the conventions the project already uses — working one folder at a time — and (3) leaves every change for the user to review. It never commits or pushes.

Two ways it's used:

  • Backfill — document a folder of undocumented models on a project that has drifted below full coverage.
  • Keep in sync — after models are added or their SQL changes (common when many contributors are landing models), run the audit to find the gap, document just those, and re-verify.

This is the systematic, coverage-driven companion to using-dbt-for-analytics-engineering (which covers one-off model building and its references/writing-documentation.md guide). Use that skill for the content principles of a good description; use this one to find the gaps and backfill them at scale in a consistent style.

Match the project's conventions — do not impose your own

Before drafting anything, read several already-documented models and mirror what you find. dbt projects vary widely; infer and follow the local house style rather than a generic template. Determine:

  • YAML layout — one shared schema file per folder (named after the folder), one .yml per model, or a single project-wide file? Add new entries where existing ones live. Only create a new file (version: 2 + models:) if the folder has none.
  • Description mechanism — inline description: strings, or {% docs %} blocks referenced with {{ doc('...') }}? Follow whichever the project uses.
  • Description shape — do descriptions lead with grain ("One row per …")? State the primary key, key foreign keys, and upstream sources? Single-line for simple staging models vs. folded blocks (description: >) for models with caveats? Copy the observed pattern.
  • Column coverage — which columns get documented (all, vs. keys + derived only)? Match the neighbours' depth.
  • Test placement — inline tests:/data_tests:, and on which columns?

Read the full file on GitHub · 138 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 11d ago First seen · 138 lines · 77 tokens per session scan A 61359d2f9fec

Subscribe to this mod's changes

maintaining-dbt-documentation is a skill published in the GitHub repository dbt-labs/dbt-agent-skills (708 stars, last pushed 2d ago), licensed Apache-2.0. It adds 77 tokens to every session and 1,877 once invoked, about $0.0004 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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