القائمة
Convert a ThoughtSpot Worksheet or Model into a Databricks Metric View. Genie Code runtime — uses ThoughtSpotClient via %run instead of ts CLI.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Convert or import a Snowflake Semantic View into ThoughtSpot as a Model. Use when Snowflake is the source and the goal is a ThoughtSpot Model — whether migrating Snowflake metrics and semantic definitions into ThoughtSpot or making a Semantic View available for Spotter and search-based analytics. Direction is always Snowflake → ThoughtSpot. Not for ThoughtSpot → Snowflake, standalone DDL generation, or adding AI context to existing ThoughtSpot models.
Convert or export a ThoughtSpot Worksheet or Model into a Snowflake Semantic View. Use when ThoughtSpot is the source and the goal is a Snowflake Semantic View — whether converting metrics and formulas for Cortex Analyst access, generating CREATE SEMANTIC VIEW DDL, writing a .sql file for later execution, or updating an existing Snowflake SV from a changed model. Direction is always ThoughtSpot → Snowflake. Not for Snowflake → ThoughtSpot, standalone TML exports, or adding synonyms/AI context to ThoughtSpot models.
Convert a Looker semantic model (LookML project) into ThoughtSpot — parses model + view .lkml files, generates Table TML and Model TML per explore, validates invariants, and imports. Optionally converts LookML dashboards to ThoughtSpot Liveboards. Direction is always Looker → ThoughtSpot.
Prepare a ThoughtSpot Model to work well with Spotter. Use when you want to improve how a Model responds to natural language queries — reviewing and writing AI context, synonyms, reference questions, business terms, and data model instructions. Mines real language from existing Liveboards, Answers, and optionally Snowflake query history to ground the coaching in how users actually talk about the data.
Convert or import a Databricks Metric View into ThoughtSpot as a Model. Use when Databricks is the source and the goal is a ThoughtSpot Model — whether migrating Databricks metrics and semantic definitions into ThoughtSpot or making a Metric View available for Spotter and search-based analytics. Direction is always Databricks → ThoughtSpot. Not for ThoughtSpot → Databricks, standalone DDL generation, or adding AI context to existing ThoughtSpot models.
Convert or export a ThoughtSpot Worksheet or Model into a Databricks Metric View. Use when ThoughtSpot is the source and the goal is a Databricks Metric View — whether converting metrics and formulas for Databricks AI/BI access, generating CREATE VIEW WITH METRICS DDL, writing a .sql file for later execution, or publishing ThoughtSpot semantics to Unity Catalog. Direction is always ThoughtSpot → Databricks. Not for Databricks → ThoughtSpot, standalone TML exports, or adding synonyms/AI context to ThoughtSpot models.
| name | ts-convert-to-databricks-mv |
| description | Convert a ThoughtSpot Worksheet or Model into a Databricks Metric View. Genie Code runtime — uses ThoughtSpotClient via %run instead of ts CLI. |
Convert a ThoughtSpot Worksheet or Model into a Databricks Metric View.
This is the Genie Code version of the CLI skill at agents/cli/ts-convert-to-databricks-mv/.
The conversion logic is identical — only the I/O layer differs.
%run ../../notebooks/ts_client
client = ThoughtSpotClient("my-profile")
All paths relative to the .assistant/skills/ root:
| File | Purpose |
|---|---|
../shared/mappings/ts-databricks/ts-to-databricks-rules.md | Column classification, aggregation, data type rules |
../shared/mappings/ts-databricks/ts-databricks-formula-translation.md | Formula translation rules |
../shared/mappings/ts-databricks/ts-databricks-properties.md | Property coverage matrix |
../shared/schemas/databricks-metric-view.md | Metric View DDL syntax and YAML schema |
../shared/schemas/thoughtspot-table-tml.md | Table TML field reference |
../shared/schemas/thoughtspot-model-tml.md | Model TML field reference |
models = client.metadata_search(type="LOGICAL_TABLE", name="%revenue%")
tml = client.tml_export(["<guid>"], fqn=True, associated=True, parse=True)
Follow the mapping rules in the shared references. The conversion logic is identical to the CLI skill — classify columns, map data types, translate formulas, generate the CREATE VIEW WITH METRICS DDL.
spark.sql(ddl_statement)
| Version | Date | Summary |
|---|---|---|
| 1.0.0 | 2026-06-15 | Initial release — Genie Code runtime |