From agentspec
Generates data quality rules, expectations, and test suites by analyzing model SQL or descriptions. Produces Great Expectations suites, dbt schema YAML, SQL assertions, and freshness checks.
How this command is triggered — by the user, by Claude, or both
Slash command
/agentspec:data-qualitydata-engineering/The summary Claude sees in its command listing — used to decide when to auto-load this command
# Data Quality Command > Generate quality rules, expectations, and test suites for your data ## Usage ## Examples --- ## What This Command Does 1. Invokes the **data-quality-analyst** agent 2. Reads model SQL or description to understand schema and business rules 3. Loads KB patterns from `data-quality` and `dbt` domains 4. Generates: - Great Expectations suite with expectations - dbt schema YAML with tests - Custom data quality SQL assertions - Freshness and completeness checks ## Agent Delegation | Agent | Role | |-------|------| | `data-quality-analyst` | Primary ...
Generate quality rules, expectations, and test suites for your data
/data-quality <model-or-description>
/data-quality models/staging/stg_orders.sql
/data-quality "Quality checks for customer dimension table"
/data-quality models/marts/
data-quality and dbt domains| Agent | Role |
|---|---|
data-quality-analyst | Primary — GE suites, quality rules, observability |
dbt-specialist | Escalation — when tests need dbt YAML format |
data-contracts-engineer | Escalation — when SLAs need formal contracts |
data-quality — Great Expectations, Soda, observability patternsdbt — dbt tests, schema YAML, custom generic testsdata-modeling — constraint patterns, referential integrityThe agent generates test definitions in your preferred format (GE, dbt, SQL) with severity classification.
npx claudepluginhub luanmorenommaciel/agentspec --plugin agentspec/validateValidates data quality on CSV, Parquet, Excel, TSV datasets using Great Expectations suites, dbt tests, or data contracts. Loads data with pandas, computes hash, checks frameworks.