dbt-model-index

dbt-model-index is a skill for Codex from OutlineDriven/outline-driven-development. It costs 35 tokens per session (865 once invoked), scanned A, original, Apache-2.0.

A guide for writing BigQuery SQL from a curated index of dbt models. dbt is a tool that builds documented data models in a warehouse such as BigQuery.

In plain words
What is it for?
Use it to translate warehouse questions into SQL against known dbt models without executing changes in the warehouse.
Why use it?
It helps queries use the right table, row level, filters, partitions, and cost limits instead of guessing from undocumented data.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to translate warehouse questions into SQL against known dbt models without executing changes in the warehouse.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/outlinedriven/outline-driven-development/dbt-model-index
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 OutlineDriven/outline-driven-development --skill dbt-model-index
Clone the repo
git clone --depth 1 https://github.com/OutlineDriven/outline-driven-development

Made for: Codex.

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-model-index

README.md
[![agentmods](https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/dbt-model-index/github.svg)](https://agentmods.dev/skills/outlinedriven/outline-driven-development/dbt-model-index)
Your own site
<a href="https://agentmods.dev/skills/outlinedriven/outline-driven-development/dbt-model-index"><img src="https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/dbt-model-index/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-model-index

Your own site · 80×15
<a href="https://agentmods.dev/skills/outlinedriven/outline-driven-development/dbt-model-index"><img src="https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/dbt-model-index.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 865 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 $0.00035 $0.00865
Opus 5 $0.00017 $0.00432
Sonnet 5 $0.00007 $0.00173
Haiku 4.5 $0.00003 $0.00086

Measured 2d ago against content hash b3754cae9edb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

dbt-model-index 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.devin/skills/dbt-model-index/SKILL.md · 43 lines

How it starts

The opening of the file, as written. The whole thing — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.

dbt model index

Contract

Field Bound contract
Trigger The user needs to query data in a dbt-powered data warehouse or resolve a data question.
Authority Read-only. No file, VCS, credential, paid, published, deployed, or remote mutation. Consults the curated model index and emits SQL without executing it.
Side effect Produces a BigQuery SQL query that references the correct model; no warehouse mutation
Done Query uses the correct fully-qualified model name, respects documented standard filters, partition fields, grain, and cost controls

Inputs

  • A data question or query intent (required). May be vague or ambiguous.
  • The human-curated model index in the Curated Model Index section (required). The human maintains one entry per dbt model, organized by domain. Each entry must record: fully-qualified table reference, grain (one row per what), useful-for query patterns, join keys, standard filters, and partition fields.
  • Standard filters, production dataset path, plan or tier valid values, and sensitive-dataset callouts documented in the Curated Model Index section (required when the project has them).

Procedure

  1. Read the data question. If it names specific models, skip to step 4. Done when: the data question is read and the path (model-named or index-scan) is determined.
  2. Scan the Curated Model Index section. Match the question to the model whose grain and useful-for patterns best fit the intent. Done when: the best-fit model is identified from the index.
  3. If no single model fits, identify the join keys that connect candidate models and note each model's grain to avoid fan-out. Done when: join keys are identified and grains noted, or a single model is selected.
  4. Construct the fully-qualified table reference using the production dataset path documented in the Curated Model Index section. For sensitive datasets, use the separate dataset path called out there. Done when: the fully-qualified table reference uses the correct dataset path.
  5. Apply every standard filter documented in the Curated Model Index section (for example, excluding test accounts, soft-deleted records, internal users, flagged or fraudulent users). Omit none. Done when: every documented standard filter is applied.
  6. For partitioned tables, filter on the partition field and constrain the date range. Never issue an unbounded scan of a large partitioned table. Done when: partitioned tables are filtered on the partition field with a bounded date range.
  7. Include a comment stating the model grain (one row per what) so join cardinality is explicit. Done when: the query includes a grain comment.
  8. If the query references plan or tier types, filter only on the valid values documented in the Curated Model Index section. Done when: plan or tier filters use only documented valid values.
  9. Emit the BigQuery SQL query. Done when: the BigQuery SQL query is emitted with correct model name, all standard filters, partition constraints, grain comment, and valid-value filters.

Read the full file on GitHub · 43 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. 2d ago Changed · -22 tokens per session b3754cae9edb
  2. 5d ago First seen · 43 lines · 57 tokens per session scan A 66e28457f137

Subscribe to this mod's changes

dbt-model-index is a skill published in the GitHub repository OutlineDriven/outline-driven-development (52 stars, last pushed 3d ago), licensed Apache-2.0. It adds 35 tokens to every session and 865 once invoked, about $0.0002 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 2026-09-03.

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