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.
npx agentmods add skills/altimateai/altimate-code/dbt-troubleshootnpx skills add AltimateAI/altimate-code --skill dbt-troubleshootgit clone --depth 1 https://github.com/AltimateAI/altimate-codeWrote 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.
[](https://agentmods.dev/skills/altimateai/altimate-code/dbt-troubleshoot)<a href="https://agentmods.dev/skills/altimateai/altimate-code/dbt-troubleshoot"><img src="https://agentmods.dev/badge/skills/altimateai/altimate-code/dbt-troubleshoot.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00050 | $0.02031 |
| Opus 5 | $0.00025 | $0.01015 |
| Sonnet 5 | $0.00010 | $0.00406 |
| Haiku 4.5 | $0.00005 | $0.00203 |
Grade A, and why
dbt-troubleshoot 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dbt Troubleshooting
Requirements
Agent: any (read-only diagnosis), builder (if applying fixes)
Tools used: bash (runs altimate-dbt commands), read, glob, edit, altimate_core_semantics, altimate_core_column_lineage, altimate_core_correct, altimate_core_fix, sql_fix
When to Use This Skill
Use when:
- A dbt model fails to compile or build
- Tests are failing
- Model produces wrong or unexpected data
- Builds are slow or timing out
- User shares an error message from dbt
Do NOT use for:
- Creating new models → use
dbt-develop - Adding tests → use
dbt-test - Analyzing change impact → use
dbt-analyze
Iron Rules
- Never modify a test to make it pass without understanding why it's failing.
- Fix ALL errors, not just the reported one. After fixing the specific issue, run a full
dbt build. If other models fail — even ones not mentioned in the error report — fix them too. Your job is to leave the project in a fully working state. Never dismiss errors as "pre-existing" or "out of scope".
Diagnostic Workflow
Step 1: Health Check
altimate-dbt doctor
altimate-dbt info
If doctor fails, fix the environment first. Common issues:
- Python not found → reinstall or set
--python-path - dbt-core not installed →
pip install dbt-core - No
dbt_project.yml→ wrong directory - Missing packages → if
packages.ymlexists butdbt_packages/doesn't, rundbt deps
Step 2: Classify the Error
| Error Type | Symptom | Jump To |
|---|---|---|
| Compilation Error | Jinja/YAML parse failure | references/compilation-errors.md |
| Runtime/Database Error | SQL execution failure | references/runtime-errors.md |
| Test Failure | Tests return failing rows | references/test-failures.md |
| Wrong Data | Model builds but data is incorrect | Step 3 below |
Step 3: Isolate the Problem
# Compile only — catches Jinja errors without hitting the database
altimate-dbt compile --model <name>
# If compile succeeds, try building
altimate-dbt build --model <name>
# Probe the data directly
altimate-dbt execute --query "SELECT count(*) FROM {{ ref('<name>') }}" --limit 1
altimate-dbt execute --query "SELECT * FROM {{ ref('<name>') }}" --limit 5
What ships with it
4 files 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.
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.
- 5d ago First seen · 188 lines · 50 tokens per session scan A 8169cef25d41
dbt-troubleshoot is a skill published in the GitHub repository AltimateAI/altimate-code (805 stars, last pushed today), licensed MIT. It adds 50 tokens to every session and 2,031 once invoked, about $0.0003 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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