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altimate-code: Skill for OpenCode

.opencode/skills/dbt-pr-review/SKILL.md

dbt-pr-review is a skill for OpenCode from AltimateAI/altimate-code. It costs 79 tokens per session (825 once invoked), scanned A, original, MIT.

A review workflow for dbt and SQL pull requests, where dbt is a tool for building data models in a warehouse. It produces an approve, comment, or request-changes decision backed by checks on lineage, result equivalence, privacy data, and model impact.

In plain words
What is it for?
It is for reviewing changed dbt models, tracing which downstream models or columns may be affected, checking whether a refactor preserves results, and identifying privacy or contract problems.
Why use it?
It helps catch downstream breakage, exposed personal data, changed query results, and costly warehouse patterns before a change is merged. The findings are tied to repeatable checks instead of relying only on reading the diff.

Skill for OpenCode

Written for OpenCode: installed under .opencode/.

This is AltimateAI/altimate-code's own configuration. It tells OpenCode how to work on altimate-code itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything altimate-code configures →

not rated 813repo +1 today A scan SkillSpector: pass 79 tokens original MIT
View source ↗ AltimateAI/altimate-code altimate.sh
Reuse

Borrowing it

Nothing to install: this file belongs to AltimateAI/altimate-code. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/AltimateAI/altimate-code/main/.opencode/skills/dbt-pr-review/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/AltimateAI/altimate-code

Made for: OpenCode.

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-pr-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/altimateai/altimate-code/dbt-pr-review/github.svg)](https://agentmods.dev/skills/altimateai/altimate-code/dbt-pr-review)
Your own site
<a href="https://agentmods.dev/skills/altimateai/altimate-code/dbt-pr-review"><img src="https://agentmods.dev/badge/skills/altimateai/altimate-code/dbt-pr-review/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-pr-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/altimateai/altimate-code/dbt-pr-review"><img src="https://agentmods.dev/badge/skills/altimateai/altimate-code/dbt-pr-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 825 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 $0.00079 $0.00825
Opus 5.5 $0.00032 $0.00330
Sonnet 5.5 $0.00016 $0.00165
Haiku 4.5 $0.00008 $0.00082

Measured 1mo ago against content hash aa78c294d98c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

dbt-pr-review 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 1mo 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.

.opencode/skills/dbt-pr-review/SKILL.md · 75 lines

How it starts

The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.

dbt PR Review

Requirements

Agent: reviewer (read-only) — also works from analyst/builder. Tools used: dbt_pr_review (primary), impact_analysis, altimate_core_equivalence, altimate_core_check, lineage_check, read-only git.

When to Use This Skill

Use when the user wants to:

  • Review a dbt pull request (changed models) before merge
  • Get a single verdict (APPROVE / COMMENT / REQUEST_CHANGES) with evidence
  • Understand the downstream blast radius of a model/column change
  • Check whether a "refactor" actually preserves results (query equivalence)
  • Catch PII exposure, contract breaks, or warehouse-cost anti-patterns pre-merge

What makes this different from a generic AI reviewer

Generic reviewers read the diff as text and guess. This review is backed by the Rust core: every blocking finding carries a deterministic proof (an equivalence counterexample, a downstream-model list, a PII classification). The verdict is signed into a replayable envelope keyed to the dbt manifest.

Workflow

  1. Run the verdict engine. Call dbt_pr_review once:

    • dbt_pr_review({}) reviews the working tree against origin/main.
    • dbt_pr_review({ base: "origin/main", head: "HEAD", manifest_path: "target/manifest.json" }) for an explicit PR range.
    • The tool reads .altimate/review.yml for the per-repo rubric and mode.

  2. Read the signed envelope. It contains the verdict, a risk tier (trivial / lite / full), and findings grouped by severity (critical / warning / suggestion), each with engine evidence.

  3. Present the verdict exactly as returned. Group findings by severity. If the run is degraded (no manifest/warehouse), state that lineage, equivalence, and data-impact were NOT verified — it is a lint-only review.

  4. Respect the safety invariant. An UNDECIDABLE equivalence result is a WARNING, never a block. Never claim a refactor is unsafe when equivalence could not be decided — recommend a data-diff instead.

Read the full file on GitHub · 75 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. 1mo ago First seen · 75 lines · 79 tokens per session scan A aa78c294d98c

Subscribe to this mod's changes

dbt-pr-review is a skill published in the GitHub repository AltimateAI/altimate-code (813 stars, last pushed today), licensed MIT. It adds 79 tokens to every session and 825 once invoked, about $0.0003 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 2026-08-30.

Code reviewDatabasesagentaibigqueryclidata-engineeringdatabricks
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