insforge-debug

The insforge-debug skill is designed to assist developers in diagnosing and resolving issues within InsForge projects, covering both frontend SDK errors and backend infrastructure problems. It provides structured guidance for identifying the root cause of errors, performance bottlenecks, and unexpected behaviors by executing appropriate diagnostic commands and surfacing relevant logs and status information. This skill is particularly useful for troubleshooting complex scenarios that involve multiple subsystems, such as combined frontend, backend, and database interactions, helping users pinpoint the source of failures efficiently.

The skill offers two main paths for diagnostics: manual and AI-assisted. The manual scenarios guide users through a series of targeted checks based on the symptom observed, such as SDK errors, HTTP status anomalies, edge function failures, slow database queries, authentication issues, real-time channel problems, and deployment failures. Each scenario focuses on surfacing logs and system status without suggesting specific fixes. The AI-assisted path, accessible via `diagnose --ai`, allows users to provide concrete problem descriptions, including error messages or failing URLs. This path returns both a diagnosis and suggested solutions, giving a rapid first-pass analysis that can be validated against underlying logs and metrics.

insforge-debug is intended for developers, DevOps engineers, and technical support personnel working with InsForge projects who need a reliable tool for systematic troubleshooting. It is suitable for a wide range of use cases, including debugging frontend SDK integration issues, backend performance optimization, monitoring edge function behavior, ensuring database query efficiency, and resolving deployment failures on Vercel. By combining structured manual checks with AI-assisted diagnostics, the skill streamlines the problem-resolution process, saving time and reducing the risk of misdiagnosis for projects of varying complexity.