Skill UI

Monadic types from samber/mo provide Go projects with Option, Result, Either, Future, IO, Task, and State abstractions to keep nulls safe, errors composable, and side effects predictable whenever you adopt functional patterns or import github.com/samber/mo.

Provides the Google Model Armor CLI to filter user-generated content and run template-guided sanitization for prompts or responses, helping teams enforce safety policies during automation workflows and schema-driven inspections.

Creates a new Google Model Armor template via `gws modelarmor +create-template`, requiring project, location, and template ID, with optional preset or JSON payload; aimed at bootstrapping safety filters before sanitization commands.

Sanitize user prompts through Google Model Armor templates via the gws CLI command, ensuring outbound safety and supporting stdin, text, or explicit JSON inputs for prompt filtering.

Sanitize Google Model Armor responses via CLI templates to ensure outbound safety before delivering model output to end users.

Provides shared GWS CLI behaviors for authentication, global flags, formatting, pagination, and safety patterns, plus zsh tips and community guidance for safely scripting workspace workloads.

This comprehensive guide outlines best practices for developing high-quality, idiomatic, and maintainable enterprise applications using Kotlin and Spring Boot. It covers architectural patterns, dependency injection using primary constructors, managing state with data classes, implementing robust RESTful APIs, handling transactions, and leveraging Kotlin features like null safety and Coroutines for asynchronous programming. It also provides guidance on modern testing strategies (Kotest, Testcontainers).

This comprehensive guide outlines essential best practices and structural checks for developing robust Salesforce Apex code. It covers critical areas such as preventing governor limit exceptions (e.g., bulk safety), enforcing security (CRUD/FLS), preventing SOQL injection, adhering to sharing models, and implementing modern Apex idioms. It also mandates rigorous testing strategies (Positive, Negative, Bulk) and proper trigger architecture.

A comprehensive guide detailing best practices for building, reviewing, and deploying Salesforce Flows. This skill covers selecting the correct Flow type (e.g., Screen, After-Save), ensuring bulk safety by preventing DML/SOQL in loops, implementing robust fault handling paths, and performing automation density checks to ensure scalable and resilient automation.

Provides comprehensive patterns and techniques for securing AI agent systems. Learn how to enforce governance policies, including tool allow/block lists, content filtering, rate limiting, and human approval workflows. Essential for building robust, compliant, and trustworthy agents in multi-agent or production environments that interact with external APIs and sensitive data.

Conducts comprehensive AI prompt safety reviews that analyze bias, misinformation, injection, and privacy risks while delivering effectiveness evaluations, security guidance, and best-practice recommendations for prompt engineers.

Explores a codebase and produces a tailored quality system: constitution, spec-aligned functional tests, review/integration/audit protocols, and AI bootstrap guidance so teams and agents share the same safety standards.