Automate auditable data-validation workflows in R using pointblank.
npx skills add https://github.com/blankuzr/R-Skills --skill r-data-validation
Please help me install this Agent Skill. Skill: r-data-validation Source: https://github.com/blankuzr/R-Skills/tree/main/gpt/skills/r-data-validation Command: npx skills add https://github.com/blankuzr/R-Skills --skill r-data-validation
Build auditable data-quality validation pipelines in R using pointblank, separating missingness, business logic, and extraction steps for traceability and reproducibility.
Define a validation contract for a dataset and implement one pointblank agent to validate missingness and cross-field rules.
High-intent search queries and answers about installing and using this skill.
Build a data validation pipeline in R by creating a pointblank agent for each source table, separating missingness checks from business logic, and interrogating results to extract failed rows for remediation.
Validate data quality in R by applying modular pointblank validation steps with stable step_ids, interrogating the results, and returning actionable validation objects that include row-level extracts of failed records.
Branch-aware missingness checks in pointblank isolate missing data patterns from cross-field business logic, assigning stable step_ids to each validation step to ensure auditable and reproducible data screening.
Use pointblank for clinical data screening by defining validation contracts that apply modular missingness and cross-field rules, interrogating results, and producing row-level extracts for downstream data cleaning workflows.
R data validation with pointblank enforces separating missingness checks from business logic to maintain traceability, assigning stable step_ids to each modular step for reproducible data-quality screening.
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