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Found 38 Skills
Plan comprehensive test data management including synthetic data generation, data anonymization, versioning, and environment-specific strategies.
Use when the user wants to create a dataset, generate synthetic data, or build a data generation pipeline.
Strategic test data generation, management, and privacy compliance. Use when creating test data, handling PII, ensuring GDPR/CCPA compliance, or scaling data generation for realistic testing scenarios.
Permission Set analysis, hierarchy viewer, and "Who has X?" auditing. Use when analyzing permissions, visualizing PS/PSG hierarchies, or finding which Permission Sets grant access to specific objects, fields, or Apex classes.
Generate synthetic test data with edge cases for ETL pipeline testing.
Generate Salesforce Flows using the MCP tool execute_metadata_action. Use when the user asks to create, build, or generate a flow — including Screen, Autolaunched, Record-Triggered (before/after-save), Scheduled. Also trigger for flow-like requests such as "when a record is created", "trigger daily at", "send an email when", "update the field when", "automate", "workflow", or "flow XML/metadata". This is the only skill for Salesforce Flow generation.
Use this skill when users need to create, generate, or modify Salesforce Sharing Rules metadata. TRIGGER when: users mention sharing rules, record sharing, criteria-based sharing, role-based sharing, guest user sharing, portal user sharing, sharingRules, sharingCriteriaRules, sharingGuestRules, sharingOwnerRules, .sharingRules-meta.xml files, or ask to share records with specific roles or groups. Also trigger when users want to configure record-level access beyond org-wide defaults (OWD), share object records with roles, groups, or guest users, or set up Experience Site guest user record visibility. SKIP when: user needs permission sets or profiles (use platform-permission-set-generate), or needs object-level security rather than record-level sharing (use platform-permission-set-generate).
현재 프로젝트의 스키마와 업무 규칙에 맞는 안전하고 일관된 가상 샘플 데이터를 생성한다. “더미 데이터 만들어줘”, “테스트 데이터를 채워줘”, “시연용 사례를 만들어줘”처럼 실제 자료 없이 화면·흐름·테스트를 확인해야 하는 요청에 사용한다. 실제 개인정보나 회사 기밀을 변형하거나 운영 데이터로 사용할 요청에는 사용하지 않는다.
Universal seed data generator: MIGRATE from ORM schemas or GENERATE from entity definitions to any target format
Use when the user asks to create ERD diagrams, normalize database schemas, design table relationships, or plan schema migrations.
Use when the user wants to create a dataset, generate synthetic data, or build a data generation pipeline.
Generate realistic synthetic data using Spark + Faker (strongly recommended). Supports serverless execution, multiple output formats (Parquet/JSON/CSV/Delta), and scales from thousands to millions of rows. For small datasets (<10K rows), can optionally generate locally and upload to volumes. Use when user mentions 'synthetic data', 'test data', 'generate data', 'demo dataset', 'Faker', or 'sample data'.