Skill UI

This comprehensive guide addresses common and complex errors encountered when automating Apple Notes on macOS using JXA or osascript. It covers three major areas: TCC permission denials, AppleEvent communication failures, and iCloud synchronization issues. The document provides a detailed error reference table, root cause analysis, tested fixes, and diagnostic scripts to help developers successfully automate Notes tasks.

A comprehensive toolkit for debugging complex Adobe API issues that resist standard troubleshooting. Covers advanced techniques such as IMS token introspection, Firefly async job failure analysis, mapping PDF Services error codes, and deep network-layer diagnostics (DNS, TLS). Essential for resolving difficult, production-level integration bugs.

A comprehensive debug bundle designed to collect diagnostic evidence from AppFolio property management API integrations. It captures essential data points including API connectivity status for properties, tenants, and work orders; authentication status using client credentials; recent integration error logs; and environment metadata. This allows support engineers to perform root cause analysis and diagnose issues like connectivity failures or authentication rejections without needing live environment access.

A comprehensive runbook providing structured guidance for rapid incident response when encountering failures with the Canva Connect API integration. It guides users through initial triage (checking status, error rates), outlines immediate mitigation strategies for common API errors (401, 429, 5xx), and covers standardized communication templates and detailed post-incident procedures, including log collection and root cause analysis.

This structured skill guides users through root-cause-first debugging when an implementer is blocked, verification fails, or repeated attempts at fixing do not converge. It mandates a systematic approach combining local evidence inspection, runtime analysis, and external documentation research to accurately classify the failure's true source (e.g., missing dependency, spec conflict). It prevents speculative patching and generates a clear, actionable fix plan.

This skill guides the comprehensive process of crash triage, enabling the assessment of vulnerability exploitability. It covers advanced techniques using debuggers (WinDbg/GDB), sanitizers (ASAN/MSAN), and interpreting low-level data like stack traces and register dumps. It is essential for vulnerability researchers analyzing crash dumps or fuzzer-generated failures to identify root causes and potential attack vectors.

This comprehensive guide serves as a complete error decoder for the OneNote Graph API. It analyzes major HTTP status codes (400, 403, 404, 429, 500, 502, 507) and provides root cause analysis, diagnostic steps, and code fixes for common issues. It specifically addresses critical failure modes like deprecated authentication methods and silent 200 OK failures, helping developers debug complex API integrations in production.

Diagnose search intent mismatches by analyzing SERP page types and user stories. This tool bridges SEO and UX, identifying ranking failures due to layout or intent issues rather than technical flaws. It provides gap analysis scores and persona-based scoring to align content with Google's rewards.

This skill automates the nf-core/pacsomatic pipeline for matched tumor-normal variant calling from BAM files. It handles input validation, samplesheet generation, dry-run checks, and submission to schedulers like Slurm or LSF. Ideal for reproducible bioinformatics analysis execution and troubleshooting pipeline failures.

This internal helper provides a language-neutral mechanism for investigating stack traces when the source language is unknown. It generates critical checks (e.g., contract checks, boundary checks), minimal reproduction steps, and potential patch targets based solely on the provided trace data, ensuring robust and comprehensive failure analysis regardless of the underlying language.

A systematic, non-mutating investigation designed for complex software failures, including bugs, regressions, crashes, and flaky behavior. This skill launches four specialized, read-only sub-agents in parallel to perform deep root-cause analysis, trace code paths, pinpoint the smallest failing seam, and predict the quickest path to confirming or fixing the issue. It is designed purely for diagnosis and hypothesis generation.

A comprehensive, four-phase methodology for debugging complex software issues. It guides users through root cause investigation, pattern analysis, hypothesis testing, and controlled implementation. The core principle emphasizes finding the underlying cause rather than applying quick, symptomatic fixes, ensuring robust and reliable code improvements across various failure scenarios.