Skill UI

A comprehensive guide covering observability patterns for service meshes like Istio and Linkerd. Learn how to implement the three pillars—Metrics, Traces, and Logs—to monitor service health, visualize dependencies, track golden signals (latency, traffic, errors, saturation), and debug microservice communication issues across complex distributed systems.

This framework provides a comprehensive methodology for defining, measuring, and implementing Service Level Indicators (SLIs), Service Level Objectives (SLOs), and managing error budgets. It helps engineering teams quantify service reliability (e.g., availability, latency) and establish clear, measurable targets (SLOs). By tracking error budgets, teams can strategically balance rapid feature development (innovation velocity) against maintaining high system stability and reliability.

This guide helps developers diagnose and fix common issues encountered when integrating the Speak API. It covers critical errors such as authentication failures, incorrect audio formats, rate limiting (429), and session expiration. The resource includes comprehensive HTTP error code reference tables, diagnostic commands (cURL, ffprobe), and resilient code patterns for implementing robust, production-ready error recovery mechanisms.

Provides SRE guidance for defining SLIs/SLOs, managing error budgets, automating toil, and configuring monitoring/alerting so teams can scale reliable services and respond to incidents effectively.

A comprehensive diagnostic guide for resolving common errors across the entire Supabase stack, including PostgREST, PostgreSQL, Authentication, and Storage. Use this tool when encountering specific error codes (e.g., PGRST301, 42501) or debugging complex API failures like RLS violations or session expiry. It provides step-by-step instructions for identifying the error layer and applying the correct fix.

A comprehensive guide for managing resource limits and quotas across all Supabase services (API, Auth, Storage, Realtime, Edge Functions). Learn how to understand tier-specific limits, configure connection pooling using Supavisor (Transaction/Session mode), and implement robust retry logic with exponential backoff to gracefully handle 429 rate limiting errors, ensuring high application reliability.

Master advanced techniques for building fault-tolerant applications integrated with Supabase. This guide implements critical resilience patterns, including circuit breakers, offline queuing (using IndexedDB), graceful degradation, exponential backoff retries, and dual-write strategies. Use this skill to handle network outages, API failures, and transient errors, ensuring your application remains highly available and reliable in production environments.

Automates SurveyMonkey surveys, responses, collectors, and analytics via Composio’s Rube MCP toolkit, guiding discovery-before-action workflows, pagination-aware fetching, error checks, and bulk processing for productivity scenarios.

This comprehensive guide demonstrates how to achieve highly testable Swift code using protocol-based dependency injection. By abstracting external concerns—such as file systems, networking, and external APIs—into small, focused protocols, developers can write deterministic unit tests that mock side effects and error paths, ensuring robust architecture across different environments (App, Test, Preview).

A disciplined debugging ritual that forces you to investigate errors, reproduce issues, and analyze patterns before proposing fixes, ensuring root causes are understood across multi-component systems and minimizing risky guesswork under pressure.

This skill helps developers adhere to Test-Driven Development (TDD) principles by generating comprehensive, failing unit and integration tests. It is specifically designed for the 'Red' phase, ensuring that expected behaviors, edge cases (null, boundary values), and error handling are rigorously defined before any implementation code is written. It forces the definition of the 'what' before the 'how'.

This skill provides a systematic, multi-step approach to identify and resolve all failing unit tests within a codebase. It guides the user through smart error grouping (e.g., grouping by ImportError or AttributeError), prioritizing fixes from infrastructure to business logic, and ensuring thorough verification to prevent regressions. Ideal for use after major refactoring, debugging CI/CD failures, or when explicitly tasked with making the test suite pass.