Skill UI

A comprehensive guide detailing common Groq API error codes (e.g., 401, 429, 400). It provides root causes, proper fixes, and code examples (Python, TypeScript) for debugging API integrations, ensuring stable operation in development environments.

A comprehensive guide for Site Reliability Engineers (SRE) covering the entire incident lifecycle. It provides structured methodologies for initial severity assessment, establishing an incident command structure, advanced observability-driven investigation (tracing, metrics, logs), systematic troubleshooting, and crucial post-incident root cause analysis (blameless post-mortems). Ideal for managing complex, large-scale system outages.

This skill outlines a comprehensive, multi-agent orchestration workflow designed for sophisticated production issue resolution. It systematically combines AI code assistants, observability platforms (like Sentry/DataDog), and automated techniques (e.g., git bisect, distributed tracing) into a rigorous four-phase process: Issue Analysis, Root Cause Investigation, Fix Implementation, and Verification. It guides best practices for reducing Mean Time To Recovery (MTTR) and improving system resilience in complex, multi-system environments.

This sophisticated skill automates the entire Pull Request (PR) quality assurance lifecycle. It systematically fetches and categorizes CI check failures and detailed review feedback using the LOGAF priority scale. The workflow guides users through root cause analysis, proposing minimal, targeted fixes, replying to reviewers, and committing updates iteratively until all checks pass, ensuring high code quality before merging.

A comprehensive diagnostic guide for resolving the 10 most common Langfuse integration errors. This resource covers root causes, specific error codes (like 401 Unauthorized or connection timeouts), and provides tested solutions for debugging missing traces, authentication failures, and general LLM observability issues.

A comprehensive quick reference guide for troubleshooting and resolving common HTTP errors (4xx, 5xx) encountered when integrating with the MaintainX API. It provides detailed root causes, diagnostic commands (using curl/jq), and specific fixes for various status codes, such as 400 Bad Request, 401 Unauthorized, 429 Rate Limit, and 500 Internal Server Error, ensuring stable application integration.

This guide provides comprehensive error handling and debugging steps for the OpenEvidence API. It covers common failure points—including authentication issues (401, 403), query validation errors (422), rate limiting (429), and service timeouts (408). Users can learn how to diagnose the root cause of connection failures and refine their clinical queries to maximize data retrieval accuracy.

This comprehensive guide helps users diagnose and fix common OpenRouter API errors, including authentication failures (401), rate limiting (429), and bad requests (400). It provides a complete reference table, detailed root causes, and executable code examples in Bash and Python to ensure stable API integration and robust error handling.

A comprehensive runbook for rapidly responding to PostHog integration failures. It provides detailed triage steps and troubleshooting guides for common API errors (401, 429, etc.), determining the root cause, and implementing graceful degradation patterns to ensure core application functionality remains stable during an outage.

This comprehensive guide teaches the best practices for writing effective, blameless postmortem reports following technical incidents. It provides a structured approach to documenting timelines, conducting root cause analysis (RCA), identifying systemic failures, and creating actionable follow-up items. Mastering this skill is crucial for fostering organizational learning and preventing future service disruptions.

Provides systematic methods for diagnosing complex, intermittent errors in the Replit environment. This guide covers advanced topics like container lifecycle issues, Nix build failures, memory leaks, and deployment crash loops using sophisticated shell scripting and runtime monitoring techniques. Use when standard troubleshooting steps fail to identify the root cause.

This skill guides you through advanced integration patterns to connect Sentry with your full observability stack. Learn how to correlate error events from structured loggers (like Winston/Pino) using Event IDs, track business metrics (counters, gauges) within Sentry, and link performance data across multiple tools (Grafana, Datadog). Achieve end-to-end visibility, ensuring every error is tied back to its root cause and business context.