Run data-quality rule checks on AIDP tables — not-null, uniqueness, allowed ranges/sets, referential integrity, and freshness. Use when the user wants to validate data, check for nulls/duplicates/orphans, assert a column's domain, or gate a pipeline on quality. Expresses each rule as bounded Spark SQL and reports pass/fail with offending counts.
安装
npx skills add oracle-samples/oracle-aidp-samples --skill aidp-data-qualitynpx skills add oracle-samples/oracle-aidp-samples --skill aidp-data-quality -a claude-code -gnpx skills add oracle-samples/oracle-aidp-samples --skill aidp-data-quality -a codex -ggemini skills install https://github.com/oracle-samples/oracle-aidp-samples.git --path ai/claude-code-plugins/oracle-ai-data-platform-workbench-engineer-agent/skills/aidp-data-qualitygh skill install oracle-samples/oracle-aidp-samples aidp-data-qualitygit clone --depth 1 https://github.com/oracle-samples/oracle-aidp-samples /tmp/oracle-samples__oracle-aidp-samples
mkdir -p ~/.claude/skills ~/.agents/skills
cp -R /tmp/oracle-samples__oracle-aidp-samples/ai/claude-code-plugins/oracle-ai-data-platform-workbench-engineer-agent/skills/aidp-data-quality ~/.claude/skills/aidp-data-quality # Claude Code
cp -R /tmp/oracle-samples__oracle-aidp-samples/ai/claude-code-plugins/oracle-ai-data-platform-workbench-engineer-agent/skills/aidp-data-quality ~/.agents/skills/aidp-data-quality # Codex, Cursor, Gemini CLI, Copilot, OpenCode