Six focused workflows for analytics engineering work.
Review SQL, profile supplied data, assess dbt health, shape data models, clarify requirements, and explain data code from the context you choose to make available in Cursor.
Honest status: the plugin source exists and works through Cursor's local-development flow. Its marketplace source is private and unpublished, so there is no public install link or download today.
Useful without a course connection.
These workflow instructions ship with the plugin. “Local-first” describes the plugin files and workspace context; the selected Cursor model may still use its configured AI provider.
/ae-review-sqlAvailable locallyWorkflow 01Review SQL
Check correctness, grain, joins, performance, and production risk.
/ae-profile-dataAvailable locallyWorkflow 02Profile data
Compute and interpret a local CSV, JSON, or JSONL profile.
/ae-review-modelAvailable locallyWorkflow 03Review a data model
Assess or propose a model from business and source evidence.
/ae-dbt-healthAvailable locallyWorkflow 04Check dbt health
Inspect a real dbt project without blindly executing dbt.
/ae-requirementsAvailable locallyWorkflow 05Clarify requirements
Turn an ambiguous request into definitions and acceptance criteria.
/ae-explainAvailable locallyWorkflow 06Explain data code
Explain selected SQL, Python, dbt, YAML, or pipeline code.
Analysis first, with visible control.
- It does not silently connect to a warehouse or mutate production.
- It does not grade, submit coursework, or provide remote hints.
- It does not include the planned AnalyticsEngineering.com backend.
- The local plugin itself contains zero anonymous telemetry.
Release updates
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