Skill UI

This guide provides comprehensive steps to diagnose and fix the most frequent Sentry SDK integration issues. It covers critical topics such as DSN validation, missing event capture, source map failures, rate limiting, and proper flushing patterns in Node.js, Python, and serverless environments. Use this when your error monitoring system is not working as expected.

A comprehensive collection of diagnostic scripts designed for troubleshooting Sentry integration failures. This bundle collects SDK versions, runtime configuration details (e.g., DSN, environment), and performs network connectivity checks to the Sentry ingest endpoint. Use it when events are not appearing in Sentry, or when systematically diagnosing complex setup issues across Node.js and Python environments.

Automates setting up distributed tracing across a microservices landscape by guiding backend selection, instrumentation strategy, and configuration generation to enable end-to-end observability and aid performance troubleshooting.

A comprehensive diagnostic bundle designed for developers integrating with the Speak API. It systematically collects critical information, including authentication status, audio format validation (checking codecs, sample rates, and file size using ffprobe), and network connectivity tests for both Speak and OpenAI endpoints. Use this tool when troubleshooting complex language learning integration issues or verifying API setup.

A comprehensive checklist designed for developers to ensure a language learning integration (Speak) is robust and ready for production deployment. It covers critical technical areas including API authentication, audio processing pipelines, rate limiting strategies, monitoring and alerting setup, and adherence to global data compliance standards (e.g., GDPR, FERPA). Use this when implementing or troubleshooting production-grade features.

This guide provides production-ready patterns for integrating the Speak language learning API. It covers managing conversation sessions, performing pronunciation assessment, preprocessing audio files using ffmpeg, implementing robust retry mechanisms (with backoff), and tracking user learning progress. Use this when developing a full-featured, high-reliability language learning application or troubleshooting complex API integrations.

A comprehensive skill for optimizing complex SQL queries, designing robust database schemas, and troubleshooting performance bottlenecks across various dialects (PostgreSQL, MySQL, etc.). Use this when queries are slow, complex set-based logic is needed (CTEs, Window Functions), or when structuring/migrating a database schema. It provides detailed query plan analysis, advanced indexing strategies, and industry best practices.

A comprehensive guide for deep PostgreSQL diagnostics, designed for advanced troubleshooting when standard methods fail. Covers using pg_stat_statements for identifying slow queries, analyzing lock contention with pg_locks, detecting connection leaks, debugging RLS policy conflicts, and profiling Edge Function cold starts. Essential for performance regression investigation and escalating issues to support.

This tool collects a comprehensive, redacted diagnostic bundle from a Supabase project. It systematically tests connectivity, authentication (Auth), Realtime capabilities, Storage buckets, and Row-Level Security (RLS) policies. The resulting archive is designed for sharing with support teams to accelerate troubleshooting of complex issues like connection failures or misconfigurations.

Automates the creation of technical troubleshooting guides by following documentation best practices, generating templates, and validating outputs for API docs, user guides, and architecture references whenever you mention troubleshooting patterns.

This guide provides comprehensive solutions for diagnosing and fixing common technical errors and exceptions encountered when using the TwinMind platform. Whether you are facing API authentication failures, microphone permission issues, transcription timeouts, rate limit exceedances, or audio format incompatibility, this reference offers step-by-step solutions and code examples to ensure smooth operation and successful integration.

A comprehensive guide for diagnosing and resolving common errors encountered when utilizing the Vast.ai platform. It provides quick references and fixes for HTTP status codes (e.g., 401, 429), instance lifecycle issues, CLI command failures, Docker image loading problems, SSH connectivity errors, and CUDA memory issues. Essential for maximizing GPU rental efficiency and debugging cloud instances.