Skill UI

Cavecrew provides a set of specialized subagents (investigator, builder, reviewer) designed for efficient code development delegation. Unlike vanilla agents, Cavecrew compresses output results, drastically reducing the token usage injected back into the main context. This allows users to maintain context over much longer, complex coding sessions, effectively preventing context exhaustion during large-scale refactoring, debugging, or multi-step feature development.

A systematic, multi-phase guide for tackling hard bugs and performance regressions. It mandates building a robust feedback loop (e.g., failing tests, harnesses), formulating falsifiable hypotheses, targeted instrumentation, and rigorous regression testing. This methodology ensures that debugging efforts are structured, efficient, and highly reproducible, making it ideal for complex software defects.

A comprehensive playbook for defeating anti-debugging mechanisms in protected binaries. Covers advanced techniques across both Linux (ptrace, /proc/self/status, timing checks) and Windows (PEB flags, NtQueryInformationProcess). Provides detailed detection methods and corresponding bypass strategies (e.g., patching, hooking, kernel modules) essential for advanced binary reverse engineering.

This toolset provides a comprehensive development workflow for iterating on MicroPython applications (such as Claude Buddy, Hello, and Snake) on the Cardputer-Adv device. It allows developers to add new apps, push single updated .py files without full re-flashing, monitor device serial logs, or execute one-shot REPL commands directly from the host machine. Essential for rapid prototyping and debugging embedded systems.

A specialized Codex CLI alias designed to check the operational status of the PUA agent or team. This tool reports current active states, corresponding Process IDs (PID), Time To Live (TTL), and identifies stale or inactive records. It is primarily used for system debugging and monitoring agent health via the command line.

Use this skill to deeply inspect and audit the entire process of local AI coding-agent sessions. It tracks critical operational metrics such as token consumption, cost spikes, tool failures, latency anomalies, and overall health scores. Ideal for debugging unreliable code runs, establishing CI/CD health gates, or comparing different attempts to ensure semantic accuracy.

This skill is designed to assist developers in debugging complex code issues. It analyzes detailed error messages, stack traces, and common error types (like TypeError or ReferenceError) to accurately pinpoint the root cause of bugs. It provides a structured, step-by-step report including specific fix suggestions and proactive prevention strategies.

Master the design, debugging, and hardening of production-grade GitHub Actions CI/CD pipelines. This skill covers advanced topics including reusable workflows, matrix builds, self-hosted runners, OIDC authentication, secrets management, environment protection, and complex trigger patterns (e.g., workflow_call, schedule, release). Use this to automate complex build, test, and deployment processes.

A comprehensive skill orchestrator designed for AI coding agents working with Go/Golang. Instead of relying on single skills, this tool analyzes the entire task context—be it designing an API, debugging a panic, or auditing security—and dynamically loads all necessary, relevant skills (e.g., concurrency, testing, error handling, and security) simultaneously. It ensures a holistic approach to Go development.

Nextflow is a powerful workflow language and runtime for building reproducible, portable, and scalable data pipelines, especially dominant in bioinformatics. This skill covers the entire workflow lifecycle: from authoring complex pipelines using the modern DSL2 syntax, to configuring containerized execution (Docker, Singularity), scaling to High-Performance Computing (HPC) or cloud environments, and running/debugging existing nf-core workflows.

This skill serves as an alias for the comprehensive debugging toolkit, enabling users to perform smart, guided debugging sessions. It assists in identifying errors, improving code quality, and walking through complex technical processes. Use it when you need structured help with debugging code in a defined environment.

This skill provides comprehensive operational capabilities for managing FrontendExtension resources in a Kubernetes cluster. It covers the entire lifecycle, including resource creation, package generation, artifact inspection, publishing, unpublishing, deletion, and deep debugging of package and publish controller behaviors. Use it for troubleshooting FE status, managing deployment pipelines, or interacting with the FE API.