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-analyzenpx skills add AltimateAI/altimate-code --skill dbt-analyzegit clone --depth 1 https://github.com/AltimateAI/altimate-codeWhat 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 | $0.00041 | $0.01036 |
| Opus 5 | $0.00020 | $0.00518 |
| Sonnet 5 | $0.00008 | $0.00207 |
| Haiku 4.5 | $0.00004 | $0.00104 |
Grade A, and why
dbt-analyze scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dbt Impact Analysis
Requirements
Agent: any (read-only analysis)
Tools used: bash (runs altimate-dbt commands), read, glob, dbt_manifest, lineage_check, dbt_lineage, sql_analyze, altimate_core_extract_metadata
When to Use This Skill
Use when the user wants to:
- Understand what breaks if they change a model
- Evaluate downstream impact before shipping
- Find all consumers of a model or column
- Assess risk of a refactoring
Do NOT use for:
- Creating or fixing models → use
dbt-developordbt-troubleshoot - Adding tests → use
dbt-test
Workflow
1. Identify the Changed Model
Accept from the user, or auto-detect:
# From git diff
git diff --name-only | grep '\.sql$'
# Or user provides a model name
altimate-dbt compile --model <name> # verify it exists
2. Map the Dependency Graph
altimate-dbt children --model <name> # direct downstream
altimate-dbt parents --model <name> # what feeds it
For the full downstream tree, recursively call children on each downstream model.
3. Run Column-Level Lineage
With manifest (preferred): Use dbt_lineage to compute column-level lineage for a dbt model. This reads the manifest.json, extracts compiled SQL and upstream schemas, and traces column flow via the Rust engine. More accurate than raw SQL lineage because it resolves ref() and source() to actual schemas.
dbt_lineage(model: <model_name>)
Without manifest (fallback): Use lineage_check on the raw SQL to understand:
- Which source columns flow to which output columns
- Which columns were added, removed, or renamed
Extract structural metadata: Use altimate_core_extract_metadata on the SQL to get tables referenced, columns used, CTEs, subqueries — useful for mapping the full dependency surface.
4. Cross-Reference with Downstream
For each downstream model:
- Read its SQL
- Check if it references any changed/removed columns
- Classify impact:
| Classification | Meaning | Action |
|---|---|---|
| BREAKING | Removed/renamed column used downstream | Must fix before shipping |
| SAFE | Added column, no downstream reference | Ship freely |
| UNKNOWN | Can't determine (dynamic SQL, macros) | Manual review needed |
What ships with it
2 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.
- 2d ago First seen · 131 lines · 41 tokens per session scan A a5a1ac6de5e0
dbt-analyze is a skill published in the GitHub repository AltimateAI/altimate-code (803 stars, last pushed 2d ago), licensed MIT. It adds 41 tokens to every session and 1,036 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 2026-08-30.
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