Skill UI

The Skill Tester is a powerful meta-skill designed for the claude-skills ecosystem. It provides comprehensive quality assurance by validating skill structure, conducting deep Python script testing (syntax, imports, runtime), and executing multi-dimensional quality scoring. It is essential for CI/CD integration, pre-commit hooks, and ensuring skills meet rigorous standards for BASIC, STANDARD, or POWERFUL tiers.

This skill provides a comprehensive, evidence-based inventory and overlap audit workflow for enterprise automation. It helps users determine which jobs, hooks, connectors, or wrappers are currently live, broken, redundant, or missing before making critical changes, ensuring reliable system architecture and clean code practices.

This guide outlines security best practices for managing Bright Data zone credentials, API tokens, and webhooks. It covers crucial steps like credential inventory, environment variable security, zone isolation across environments, scheduled credential rotation, and implementing pre-commit hooks to prevent sensitive data leakage, maximizing data security and compliance.

A comprehensive solution for monitoring CoreWeave cluster events and GPU workload status using webhooks. It tracks critical lifecycle events such as pod readiness, job completion, volume attachment, and node health. Essential for building automated scaling, alerting, and recovery pipelines for large-scale GPU-accelerated inference and training workloads.

This guide provides methods for robust monitoring and automation tailored for services deployed on Fly.io. It covers key areas including polling the Machines API to detect state changes, implementing comprehensive health check endpoints, processing structured logs using tools like `jq`, and automating deployment notifications within CI/CD pipelines. Essential for achieving high availability and reliable operations.

A comprehensive guide for managing the full lifecycle of OpenKruise within the KubeSphere platform. This skill assists users with installation, upgrading, querying status (CRDs, Pods, logs), generating manifests for advanced workloads (SidecarSet, CloneSet), performing rollouts, and troubleshooting complex runtime issues like webhooks or missing configurations, utilizing both kubectl and KubeSphere APIs.

This skill provides a deep dive into the architecture of low-level keyloggers. It covers techniques such as kernel driver hooks, using WH_KEYBOARD_LL, ETW-based input capture, and analyzing user-mode vs. kernel-mode approaches. Use this methodology to understand input capture mechanisms, research EDR evasion methods, or analyze malware architecture for advanced security threat detection.