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AI Tools & Skills

DQX ships Agent Skills that teach AI assistants how to use the library correctly. They're small, focused Markdown files with YAML frontmatter — the open format supported by Databricks Genie Code, Claude Code, and any other tool that follows the standard.

The skills live in the skills/ directory of the DQX repo.

What's included​

SkillWhat it coversCanonical docs
dqx-define-checksCreating quality rules — DQRowRule, DQDatasetRule, DQForEachColRule, YAML / dict metadata formQuality Checks Definition
dqx-apply-checksValidating a DataFrame or table against a set of rulesApplying Quality Checks
dqx-end-to-endRead → check → write in one call with apply_checks_and_save_in_tableEnd-to-end apply
dqx-profile-and-generateProfiling and generating rule candidates with DQProfiler / DQGeneratorData Profiling
dqx-storageLoading / saving checks across file, workspace, volume, table, installation, and Lakebase backendsLoading and Storing Quality Checks

Each skill is a folder containing a single SKILL.md with the standard name + description frontmatter. Tools auto-load skills based on the description; users can also invoke them explicitly (@dqx-define-checks, slash commands, etc.) depending on the tool.

Installing DQX skills​

Clone the DQX repository in your workspace using a Git folder, then copy the skills/ folder into a workspace-level or user-level skills directory:

# Option A — workspace-wide (all Genie Code users see these)
databricks workspace import-dir skills /Workspace/.assistant/skills

# Option B — current user only — substitute your workspace email below
databricks workspace import-dir skills /Users/<your-email>/.assistant/skills

Genie Code picks up skills from these directories automatically. Use the following prompt with Agent mode to confirm:

"List the DQX skills you can use."

The skill fires when its description matches your request. Use @ to manually invoke a specific skill (e.g. @dqx-define-checks add a uniqueness check on order_id).

See the Databricks Genie Code Documentation for more details.

Using DQX skills​

After installing DQX skills, you can either let your tool use skills automatically or invoke them by name. Typical prompts:

Add a DQX uniqueness check on (order_id, line_item_id) to my pipeline.
Split my bronze table into valid and quarantine outputs using these rules: …
Profile catalog.schema.orders and suggest quality checks.
Load DQX checks from a Delta table and apply them to a streaming DataFrame.

Agents will load the relevant skill into context, follow its patterns, and link back to the canonical documentation for anything outside the skill's scope.

Extending DQX skills​

DQX's agent skills are scoped to DQX's public APIs. Follow these guidelines when extending them:

  • Skills should stay short; the full SKILL.md is loaded every time the skill fires, so every line costs tokens on every invocation.
  • Prefer linking to /docs/... over duplicating content; the skill's job is to tell the model when and how to use the API, not to reprint the reference.
  • Always import from databricks.labs.dqx.* — never guess module paths.
  • Point to the canonical documentation for any topic outside the skill's core responsibility.
  • Changes to the public DQX API should be reflected in the matching skill in the same PR. See Contributing for the full workflow.

Source​