Skill UI

This agent analyzes a Monte Carlo monitor's report and configuration to identify alert patterns. It recommends concrete configuration changes for metric, custom SQL, validation, and table monitors, helping reduce false positives and alert fatigue without sacrificing real signal.

This skill runs an automated evolution process designed to systematically optimize the seven core policy surfaces of an AI agent harness (e.g., planner, contextBuilder, reviewer). By mutating these policies and scoring the variants in a sandbox, it identifies crucial performance improvements without requiring expensive foundation model retraining. It is ideal for empirical configuration tuning and establishing optimized baselines.

Provides comprehensive configuration management for local LLM inference using RuVLLM. Users can select models, perform task-specific fine-tuning with MicroLoRA adapters, or implement continuous, real-time adaptation using SONA. This tool guides the entire advanced LLM workflow, covering status checks, configuration generation, and advanced adaptation loops.

A comprehensive guide to PostgreSQL best practices, covering advanced indexing (GIN, BRIN, Partial), schema design, performance tuning, and security implementation (RLS). It details optimizing common SQL patterns like cursor pagination and UPSERT, essential for building high-performance, reliable database systems.