Skill UI

Master essential Bash scripting and Linux command-line operations including file management, process control, text processing, and network utilities. Ideal for automating tasks, debugging, and system administration on macOS and Linux environments.

This skill enables AI to adapt its operational behavior based on specific task types such as brainstorming, coding, debugging, reviewing, teaching, and deployment. It optimizes performance by switching between distinct modes like BRAINSTORM, IMPLEMENT, and DEBUG, ensuring appropriate communication styles and output formats for each scenario.

This skill covers comprehensive patterns and techniques for analyzing compiled binaries, understanding assembly code, and reconstructing program logic. It includes x86-64 and ARM assembly conventions, control flow structures, data access patterns, and common code optimizations. Useful for reverse engineering, security auditing, and low-level debugging tasks.

An evidence-first procedure for system performance debugging, root-cause analysis and incident reports. Applies Brendan Gregg's USE and TSA methods to sweep resources and thread states, then drills down with off-CPU analysis and flame graphs, ending in triage notes, RCA reports or blameless postmortems.

This comprehensive skill guides users through the entire debugging lifecycle, from reproducing elusive bugs to tracing the root cause, implementing permanent fixes, and preventing future regressions. It covers advanced techniques like binary search, time travel debugging, and handling common patterns such as race conditions and null values, ensuring professional and systematic troubleshooting for any production issue.

Provides expert review and implementation of C systems code with explicit memory ownership, pointer bounds, error handling, and measured performance. Covers POSIX compliance, embedded systems, multithreading, and debugging with valgrind and gdb.

This skill transforms completed debugging sessions or repeated corrections into evidence-backed procedures. It captures reusable lessons upon explicit request, ensuring privacy by not automatically saving memories. Users must provide session summaries or transcripts to identify failures and verify fixes. The output is a reviewed procedure suitable for documentation, excluding secrets and personal details. It helps maintain knowledge without modifying agent configuration automatically.

This skill enables AI agents to control the user's visible browser interface directly. It supports navigation, clicking, typing, and debugging actions within the browser pane. The agent can take screenshots, interact with web tools, and handle login processes. It operates via a live Automation REPL without requiring code mode, ensuring safe and scoped interactions within the current session.

Comprehensive reference for configuring and using Claude Code, covering project instructions (CLAUDE.md), advanced features like debugging and thinking keywords, and best practices for iterative development and efficient context management.

Four-phase debugging methodology with root cause analysis. Use when investigating bugs, fixing test failures, or troubleshooting unexpected behavior. Emphasizes NO FIXES WITHOUT ROOT CAUSE FIRST.

This skill applies a rigorous, evidence-first discipline to coding tasks, inspired by Fable-like best practices. It guides agents through a structured workflow: inspecting the workspace, tracking goals and findings, grounding all conclusions in verifiable evidence, and executing thorough verification gates before declaring completion. Ideal for complex development, debugging, or adapting cross-model prompt guidance into robust, verifiable project rules.

Troubleshooting guide for Kubernetes pods in crs namespace experiencing CrashLoopBackOff, OOMKilled, cascade failures, or Redis issues. Includes commands for pod status, events, logs, resource pressure analysis, and Redis debugging to diagnose and resolve critical infrastructure failures.