Skill UI

Simulates Ilya Sutskever, delivering safety-first AGI insights on consciousness, scaling laws, deep learning, and OpenAI’s high-stakes moments.

Provides encoded expertise for multi-location retailers to forecast demand, set safety stock, plan replenishment, and model promotional lifts using ABC/XYZ analysis, volatility-aware safety stock, and supplier-aware reorder logic.

YES.md is an AI governance engine that layers safety gates, evidence-based debugging, anti-slack detection, and machine-enforced hooks so assistants verify fixes, avoid guesses, and document consequences before touching configs, deployments, or sensitive data.

Design reference that lays out 98 rules for AI-native CLI tools, covering JSON-first output, structured errors, safety guardrails, agent metadata, and certification layers for trustworthy automation.

Guide for configuring Google Workspace advanced phishing and malware protections through Gmail safety settings, attachment safeguards, spoofing checks, enhanced browsing, and APP enrollment to harden high-risk accounts.

PydanticAI brings Pydantic-style validation and type safety to LLM agent workflows, offering structured outputs, dependency injection, and tool integrations across providers so Python teams can test, monitor, and reuse agents reliably.

Automated harness for healthcare deployments that runs Jest suites across CDSS logic, PHI exposure, data integrity, clinical workflow, and integration gates, aborting releases on any critical failure to keep patient safety non-negotiable.

Checklist for securing Solidity AMMs, detailing reentrancy defenses, CEI ordering, donation manipulation guards, oracle hardening, slippage checks, reserve math safety, and audit tooling for liquidity pools and swap flows.

Prevents silent decimal mismatches across EVM chains by querying runtime decimals, caching per chain/token, and normalizing balances for bots, dashboards, and DeFi tooling.

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.

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.