Skill UI

A comprehensive guide to setting up a local development loop for building and testing MaintainX integrations. This workflow utilizes TypeScript, hot reloading, mock API servers, and automated unit/integration testing. It provides a sandboxed environment for developers to efficiently develop and debug their services.

Used for building, debugging, and extending MCP servers and clients. This skill implements robust connections between AI systems and external tools/data sources using structured protocols like JSON-RPC 2.0. Expertise includes defining tool schemas (Zod/Pydantic), configuring transport layers (HTTP/SSE/stdio), and scaffolding full-stack projects in TypeScript or Python.

A comprehensive guide for diagnosing and fixing common errors and exceptions encountered when using the Mistral AI API. Covers critical topics such as 401 Unauthorized, 429 Rate Limiting, invalid model IDs, context length limits, and server errors, providing actionable fixes and code snippets for developers.

Delivers end-to-end monitoring setups—structured logging, Prometheus/Grafana dashboards, alerting rules, distributed tracing, and load/profile testing—so teams can observe services, debug production issues, and plan capacity.

Guides you through diagnosing Next.js getServerSideProps, getStaticProps, and API route failures by checking terminal logs, adding explicit try-catch handling, and reviewing hosting logs or common causes like env vars, DB, or serialization issues.

A comprehensive guide for developers to diagnose and fix the six most common errors encountered when building Obsidian plugins. It covers critical technical issues such as null pointer exceptions, manifest loading failures, incorrect CSS paths, command registration timing, and state persistence bugs, ensuring reliable and stable plugin functionality.

This guide establishes a comprehensive and rapid development loop for Obsidian plugins. It covers the entire workflow, from setup (cloning templates, symlinking) to advanced features, including running esbuild in watch mode, achieving hot-reloading (via Ctrl+R or automatic methods), deep debugging with Chrome DevTools, and running unit tests with vitest. Essential for developers seeking fast feedback and reliable plugin iteration.

This skill provides a comprehensive guide to setting up isolated development, testing, and production vaults within Obsidian. It covers advanced techniques like symlinking plugin sources for hot reloading, implementing environment-specific configuration logic (e.g., managing debug modes and feature flags), and creating standardized vault templates for team onboarding, ensuring a robust and scalable development lifecycle.

A comprehensive toolkit for implementing production-grade observability in Obsidian plugins. It provides structured logging with log levels and history, a robust metrics collector (supporting counters, gauges, and timers for performance tracking), and an error tracker with deduplication. Users can build a real-time debug panel to monitor plugin performance, diagnose issues, and set up comprehensive error reporting.

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 bundle collects comprehensive diagnostic evidence from the OpenEvidence clinical decision support API. It validates API credentials, checks query endpoint health, retrieves evidence citations, and captures model metadata. Use it to diagnose complex issues like query failures, missing references, or high latency without needing direct dashboard access.

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.