What is domo-import-to-snowflake?

A migration helper that copies Domo datasets into Snowflake when they do not already have a warehouse table. Domo is a business analytics platform, while Snowflake is a cloud data warehouse that Sigma can query.

Use it for Domo datasets marked as landed data: extract their rows, create Snowflake tables, and patch `dataset-map.json` so Domo-to-Sigma can continue.

It fills the missing warehouse source instead of guessing where API data, webform data, Excel uploads, or sample data should come from. It then updates the dataset map so the rest of the migration can use the new table.

domo-import-to-snowflake — Skill for Claude Code by twells89

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 twells89/sigma-migration-skills --skill domo-import-to-snowflake

Clone the repo

git clone --depth 1 https://github.com/twells89/sigma-migration-skills

Made for: Claude Code.

Or install domo-to-sigma, the plugin that ships this one along with the rest of its 3 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/twells89/sigma-migration-skills/domo-import-to-snowflake/github.svg)](https://agentmods.dev/skills/twells89/sigma-migration-skills/domo-import-to-snowflake)

Your own site

<a href="https://agentmods.dev/skills/twells89/sigma-migration-skills/domo-import-to-snowflake"><img src="https://agentmods.dev/badge/skills/twells89/sigma-migration-skills/domo-import-to-snowflake/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/twells89/sigma-migration-skills/domo-import-to-snowflake"><img src="https://agentmods.dev/badge/skills/twells89/sigma-migration-skills/domo-import-to-snowflake.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,431 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.

Model	Per session	Once invoked
Fable 5.1	$0.00000	$0.01431
Opus 5	$0.00000	$0.00715
Sonnet 5	$0.00000	$0.00286
Haiku 4.5	$0.00000	$0.00143

Measured 12d ago against content hash 60112920c5f1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

domo-import-to-snowflake 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 12d ago.

The scan reads SKILL.md. This mod also ships 10 executable files (scripts/domo_import_to_snowflake.rb, scripts/lib/domo_extract.rb, scripts/lib/landing_manifest.rb, …), 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.

plugins/domo-to-sigma/skills/domo-import-to-snowflake/SKILL.md · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Domo (landed data) → Snowflake

Sigma is warehouse-native: every DM table resolves as live SQL against a connected warehouse. domo-to-sigma's build-dm.rb already knows how to auto-fill discovery/dataset-map.json for connector-backed DataSets (Domo's own Snowflake connector carries databaseName/schemaName/tableName in its stream config), but a DataSet landed directly into Domo — API, webform, Excel upload, or Domo's own sample/demo content — has no warehouse table at all. build-dm.rb flags this rather than guessing: the entry gets _source: "domo-landed-data" and an unmistakable sentinel table name, <TABLE:LANDED_DATA_NO_WAREHOUSE_SOURCE>. This skill extracts that DataSet's rows and lands them in Snowflake, then patches the entry in place so the very next build-dm.rb run resolves it like any other DataSet.

Two tracks, one migration (this skill is track 1):

1. DATA   (this skill)      domo-landed-data DataSets → Snowflake tables + dataset-map.json patched
2. LOGIC  (domo-to-sigma)   Beast Modes / cards / layout → Sigma dashboard — unchanged

Track 2 needs no separate repoint step: build-dm.rb already reads dataset-map.json directly, so once this skill patches an entry, the next build-dm.rb/migrate-domo.rb run just works.

Skip this skill for connector-backed DataSets — they already resolve via build-dm.rb's existing stream-config auto-fill.

What it does

scripts/domo_import_to_snowflake.rb (generic — no hardcoded dataset ids):

Select — reads the sibling domo-to-sigma skill's discovery/dataset-map.json; auto-detects every _source: "domo-landed-data" entry, or takes an explicit --dataset-id subset.
Extract + schema — Domo.query_dataset(id, sql), paginated explicitly, with a measured COUNT(*) row-count parity check (never assumed). Column types come from the same response's metadata[].type (paired positionally with columns), not Domo.dataset(id)['schema'] — live validation found that field empty for 9 of 10 real sample DataSets. See refs/type-mapping.md for the Domo → Snowflake type table and refs/live-validation.md for what was confirmed live.
Load — typed CREATE TABLE + snow sql PUT/COPY INTO, then a GRANT SELECT (default role PUBLIC, overridable).
Sync — --sigma-connection <uuid> triggers POST /v2/connections/<id>/sync once after the whole batch, so new tables resolve immediately.
Patch — rewrites the landed entries' database/schema/table and _source in dataset-map.json (see refs/naming-and-sentinel.md). connectionId is never touched — same rule as every other entry type.

Read the full file on GitHub · 97 lines

Files

What ships with it

15 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.

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.

12d ago First seen · 97 lines · 0 tokens per session scan A 60112920c5f1

Subscribe to this mod's changes

domo-import-to-snowflake is a skill published in the GitHub repository twells89/sigma-migration-skills (16 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,431 tokens. 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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