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Found 91 Skills
Standardize and format phone numbers with international support, validation, and multiple output formats.
Working effectively with JSON data structures.
Migrates JSON Schemas between draft versions for use with z-schema. Use when the user wants to upgrade schemas from draft-04 to draft-2020-12, convert between draft formats, update deprecated keywords, replace id with $id, convert definitions to $defs, migrate items to prefixItems, replace dependencies with dependentRequired or dependentSchemas, adopt unevaluatedProperties or unevaluatedItems, or adapt schemas to newer JSON Schema features.
Pydantic models and validation. Use when: (1) Defining schemas, (2) Validating input/output, (3) Generating JSON schema.
Data analysis, visualization, and storytelling skill for financial and RevOps contexts. Use when: analyzing revenue data, building forecasts, cohort analysis, churn modeling, pipeline analytics, creating data-driven reports, building dashboards, cleaning messy data, sanity-checking analytical claims, exporting to Excel with formulas, or extracting data from PDFs. Features decision logging, bias-aware interpretation, and progressive disclosure (slide deck -> detailed report -> full notebook with all decisions documented).
OmniStudio Data Mapper (formerly DataRaptor) creation and validation with 100-point scoring. Use when building Extract, Transform, Load, or Turbo Extract Data Mappers, mapping Salesforce object fields, or reviewing existing Data Mapper configurations. TRIGGER when: user creates Data Mappers, configures field mappings, works with OmniDataTransform metadata, or asks about DataRaptor/Data Mapper patterns. DO NOT TRIGGER when: building Integration Procedures (use sf-industry-commoncore-integration-procedure), authoring OmniScripts (use sf-industry-commoncore-omniscript), or analyzing cross-component dependencies (use sf-industry-commoncore-omnistudio-analyze).
Authors and structures professional-grade agent skills following the agentskills.io spec. Use when creating new skill directories, drafting procedural instructions, or optimizing metadata for discoverability. Don't use for general documentation, non-agentic library code, or README files.
Performs technical SEO audits covering site speed, crawlability, indexability, mobile-friendliness, security, and structured data. Identifies technical issues preventing optimal search performance.
Design ETL workflows with data validation using tools like Pandas, Dask, or PySpark. Use when building robust data processing systems in Python.
Compare two datasets to find differences, added/removed rows, changed values. Use for data validation, ETL verification, or tracking changes.
Expert for developing Streamlit data apps for Keboola deployment. Activates when building, modifying, or debugging Keboola data apps, Streamlit dashboards, adding filters, creating pages, or fixing data app issues. Validates data structures using Keboola MCP before writing code, tests implementations with Playwright browser automation, and follows SQL-first architecture patterns.
Use this for SQL queries, database schema design, ETL pipelines, data transformations (pandas/Spark), and data validation.