Skill UI

This tool performs a rigorous Level 2 semantic epistemic review of Agent-Native Research Artifacts (ARAs). It assesses six critical dimensions—including evidence relevance, falsifiability, and methodological rigor—to determine the content's intellectual soundness. It is used after initial structural validation to provide objective, constructive criticism, scoring the work from Strong Accept to Reject.

This framework enforces high output quality, intellectual honesty, and continuous improvement across all AppSec agents. It mandates structured processes, including self-critique loops, anti-rationalization guards, and self-reflection quality gates (≥8 scoring). Applicable during code review, SAST, SCA, and threat modeling, it ensures rigorous and verifiable security analysis.

A comprehensive guide for building high-performance GraphQL servers using Golang. This skill covers everything from choosing between gqlgen and graphql-go, designing robust schemas (nullability, pagination), implementing clean resolver patterns, and critically, preventing N+1 database query issues using DataLoaders. Essential for backend engineers building enterprise-grade APIs.

Expert assistance for building, modifying, and debugging Minecraft server plugins for the Paper, Spigot, and Bukkit ecosystems. This includes implementing complex gameplay mechanics such as minigames, advanced combat systems, persistent player progression (perks, economy, quests), custom command handling, and robust state management. We handle configuration, listener registration, and adherence to best practices for Java-based server API usage.

This skill performs comprehensive, feature-level integration validation after all associated development tasks are implemented. It goes beyond checking individual tasks to ensure cross-task consistency, full test suite passage, and complete specification coverage. It validates data flow, architectural adherence, and performs critical security scans for residual issues (e.g., TODOs, hardcoded secrets), providing a holistic GO/NO-GO assessment for deployment. Use this skill as a final quality gate to verify that the completed feature set respects the designed boundaries and dependencies end-...

This tool assists engineers in transforming vague work logs into structured, evidence-backed impact statements for professional documentation. It uniquely mines Copilot CLI session logs, git commits, and GitHub PRs to reconstruct forgotten work. It enforces a mandatory 'Action → Result → Evidence' impact contract, making it indispensable for preparing performance reviews, promotion packets, and self-assessments.

A reflection-based Dependency Injection (DI) container for Go. It is designed to facilitate the wiring of complex object graphs during application startup. Developers can use `Provide` to register constructors and manage dependencies using structures like `dig.In` and `dig.Out`. It supports named values, value groups, and interfacing, making it ideal for building robust, scalable, and highly testable Go applications and libraries.

A robust application framework for Go, built on the uber-go/dig container. It provides advanced features essential for long-running services, including structured dependency injection, explicit lifecycle hooks (OnStart/OnStop), modular composition, and signal-aware graceful shutdown handling. Ideal for building robust daemons, HTTP servers, and background workers.

This skill performs a rigorous, 5-dimension expert critique on any digital artifact, such as landing pages, presentations, or prototypes. It systematically evaluates five critical areas—Philosophy, Visual Hierarchy, Detail Execution, Functionality, and Innovation—scoring each 0-10. The output is a comprehensive, evidence-backed HTML report providing actionable insights, a radar chart, and prioritized lists (Keep/Fix/Quick-wins) to guide systemic design improvements.

KubeStellar Console is an open-source, multi-cluster Kubernetes dashboard (CNCF project) that provides advanced operational capabilities powered by an MCP server and built-in AI agent skills. It helps manage complex deployments across edge and cloud environments, offering AI-assisted troubleshooting, performance testing, and deep integration with major CNCF projects like Argo and Istio.

Logic Lens is an advanced AI skill that performs deep, formal logic-driven code review. Unlike standard linters, it analyzes code for complex issues like race conditions, security vulnerabilities (SQL injection, XSS), type safety flaws, and algorithmic errors across 9 critical risk categories. It is ideal for pre-merge PR reviews, auditing sensitive code paths, and refactoring complex business logic.

Squirrel is an advanced, full-cycle AI coding skill designed to guide software development from concept to production. It automatically detects the current project state (greenfield, in-progress, or mature) and adapts an 8-phase engineering pipeline. This comprehensive workflow covers planning, building, rigorous testing, bug hunting, code polishing, documentation, and deployment readiness, ensuring high-quality, maintainable results.