Skill UI

Design, implement, debug, and optimize API integrations with resilient, observable, production-ready patterns for REST, GraphQL, webhooks, and authentication flows.

Create, modify, debug and deploy Apify Actors with the apify CLI. Covers template selection in JS/TS/Python, input/output schemas, runtime logic, local testing, secrets handling and secure deployment.

This skill provides comprehensive patterns and techniques for analyzing compiled binaries and understanding assembly code. It covers x86-64, ARM, and calling conventions, helping users reconstruct program logic. Use it for reverse engineering tasks, security analysis, and debugging low-level code.

This skill provides a methodical approach to system performance troubleshooting and root-cause analysis using Brendan Gregg's USE and TSA methodologies. It guides users through evidence-backed investigation steps, from initial triage to detailed thread state analysis, ensuring every claim is supported by metrics. Ideal for SREs and DevOps engineers debugging latency, CPU, memory, or network issues on Linux systems, culminating in structured RCA reports or postmortems.

Systematically reproduce, diagnose, and fix bugs using evidence-based debugging techniques, then add regression tests to prevent recurrence.

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.

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 that traces bugs to their root cause before fixing. Use for test failures, runtime errors, intermittent issues, and unexpected behavior.

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.

Debugging tool for Kubernetes pod failures including CrashLoopBackOff, OOMKilled, and cascade failures. Provides commands to diagnose Redis issues, resource pressure, and service restarts in the crs namespace. Includes triage workflow, log analysis, and cascade detection for production cluster troubleshooting.

Expert in root cause analysis for errors, test failures, and unexpected behavior. Captures error messages, identifies reproduction steps, isolates failure locations, implements minimal fixes, and verifies solutions. Provides root cause explanations, evidence, code fixes, testing approaches, and prevention recommendations.