Loading...
Loading...
Found 91 Skills
Data format specialist covering TOON encoding, JSON/YAML optimization, serialization patterns, and data validation for modern applications. Use when optimizing data for LLM transmission, implementing high-performance serialization, validating data schemas, or converting between data formats.
Implements WPF data validation using ValidationRule, IDataErrorInfo, and INotifyDataErrorInfo. Use when building forms, validating user input, or displaying validation errors in UI.
Expert guide for Schema.org structured data and JSON-LD implementation. Use when creating schema markup, validating structured data, implementing rich results (FAQ, HowTo, Product, Article, LocalBusiness, Breadcrumb, Organization, etc.), troubleshooting rich snippet eligibility, or understanding Google's structured data requirements.
Implement masked text input controls in WinForms applications. Use this skill whenever the user needs to create input fields with format masks (phone numbers, IP addresses, dates, currency), validate formatted input, restrict data entry to specific patterns, or configure how user input behaves with mask constraints.
Assess data quality with checks for missing values, duplicates, type issues, and inconsistencies. Use for data validation, ETL pipelines, or dataset documentation.
Data quality framework covering completeness, accuracy, consistency, validation rules, and data contracts. Use when implementing data validation, setting up data quality checks, or defining data contracts.
Migration Architect
Validate at every layer data passes through to make bugs impossible. Use when invalid data causes failures deep in execution, requiring validation at multiple system layers.
Zod schema validation patterns and type inference. Auto-loads when validating schemas, parsing data, validating forms, checking types at runtime, or using z.object/z.string/z.infer in TypeScript.
Use to define schemas, topic tags, and lineage metadata for enriched signals.
Health check your knowledge base — find broken links, missing metadata, gaps
Use this skill when implementing data validation, data quality monitoring, data lineage tracking, data contracts, or Great Expectations test suites. Triggers on schema validation, data profiling, freshness checks, row-count anomalies, column drift, expectation suites, contract testing between producers and consumers, lineage graphs, data observability, and any task requiring data integrity enforcement across pipelines.