Skill UI

A comprehensive guide for managing Documenso integration incidents. It provides step-by-step procedures for diagnosing and resolving production outages, covering cloud service disruptions, self-hosted database errors, and webhook failures. Essential for on-call engineers to maintain system uptime.

This skill provides expert-level diagnostic capabilities for complex distributed systems. It specializes in analyzing production incidents, identifying deep root causes, and designing comprehensive observability solutions. Use this when investigating recurring errors, reviewing system logs/traces, and implementing preventative reliability measures.

This skill acts as an expert guide for implementing comprehensive error monitoring and observability solutions. It covers setting up robust error tracking systems, configuring intelligent alerts, implementing structured logging, and establishing advanced error grouping and recovery strategies. Use it to enhance production stability and accelerate issue resolution.

A comprehensive runbook providing systematic procedures for responding to Firecrawl API outages and integration failures. It guides technical teams through triage, diagnosis, and mitigation for common issues (e.g., 401, 429, 5xx errors). Includes steps for fallback implementation, evidence collection, and postmortem documentation to ensure rapid service recovery.

A comprehensive checklist for securely deploying and validating applications using Firecrawl's core APIs (scrape, crawl, map, extract) in a production environment. It covers critical areas including secure credential management, implementing crawl safety limits, robust error handling (rate limits, authentication failures), establishing monitoring alerts, and executing necessary rollback procedures.

A comprehensive runbook providing standard operating procedures for handling Granola service disruptions, ranging from minor recording failures and sync errors to full organizational outages. It guides users and IT admins through triage (P1-P4 severity), detailed remediation steps, and escalation paths to ensure business continuity.

This comprehensive runbook guides incident response for Groq API failures. It covers triage steps, severity classification (P1-P4), troubleshooting decision trees (e.g., handling 429 errors or 5xx outages), and implementing immediate mitigations like model fallback or key rotation. Use this when responding to Groq outages to restore service stability.

A comprehensive operational runbook for managing outages and errors related to Mistral AI integrations. It provides structured procedures, including severity classification, quick API health checks, decision trees for common errors (401, 429, 5xx), immediate mitigation steps, and post-incident evidence collection and reporting.

This skill provides a comprehensive framework for monitoring Mistral AI API usage in production. It includes an instrumented client wrapper (TypeScript) to automatically capture critical metrics like latency, token consumption, cost, and error rates. Furthermore, it integrates with Prometheus for metric storage and Grafana for visualization, allowing users to set up sophisticated alerting rules for performance degradation, rate limiting, or cost spikes.

This skill guides the implementation of comprehensive, real-time monitoring for APIs. It covers collecting key metrics (latency, error rates, request rate), setting up health and readiness endpoints, building detailed Grafana dashboards, and implementing SLO-based alerting (following the RED method). Use this when you need to ensure API reliability, high availability, and performance in a production environment.

This skill specializes in implementing Service Level Objectives (SLOs) and Service Level Indicators (SLIs) to enforce reliability standards. It guides users in designing comprehensive SLO frameworks, calculating error budgets, and building robust monitoring systems. Use this when you need to establish data-driven reliability targets, balance feature velocity with technical health, and align service performance directly with core business objectives.

Provides a comprehensive monitoring solution for the Perplexity Sonar API. It tracks critical performance metrics, including latency (p95), cost per query, error rates, and citation quality. This skill is essential for implementing production monitoring dashboards, configuring proactive alerts (e.g., high latency, zero citations), and ensuring the API's stability and high-quality output in real-world applications.