kotzilla

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1. 9/27/2026

   Updated: best for, features, integrations, limitations, platforms, summary, use cases, walkthrough

   See recorded changes

   bestFor

   Before: ["Android and Kotlin Multiplatform development teams seeking deep observability and AI-assisted issue remediation."]

   After: ["Android and Kotlin Multiplatform development teams seeking deep observability and AI-assisted remediation beyond traditional tools like Firebase."]

   features

   Before: ["Automatic issue detection for crashes, ANRs, slow startups, and performance issues.","Unified crash reporting across all Kotlin Multiplatform targets including iOS with fully desymbolicated stack traces.","Performance monitoring identifying slow startups, ANRs, frozen screens, and correlating them with blocking components.","Visualization of Koin dependency graphs to improve maintainability and ensure runtime-safe code.","AI-powered remediation connecting AI coding assistants to find root causes and apply accurate fixes via the MCP Server."]

   After: ["Crash reporting unified across all Kotlin Multiplatform targets including iOS with fully desymbolicated stack traces and one SDK configuration.","Performance monitoring identifying slow startups, ANRs, and frozen screens correlated with blocking ViewModels or heavy component resolutions.","Visualization of Koin dependency graphs ensuring real-time compile safety for maintainable and runtime-safe code.","AI-powered remediation connecting AI coding assistants via the MCP Server to find root causes and apply accurate fixes using natural language.","Full production visibility providing real-time insights on components, threads, and memory to quickly detect and understand app issues and crashes."]

   integrations

   Before: ["Integrates with AI coding assistants such as Claude Code, Cursor, Copilot, Gemini, and others via the MCP Server."]

   After: ["Works with popular AI coding assistants such as Copilot, Gemini, Claude, and others via the MCP Server."]

   limitations

   Before: ["Requires use of Koin dependency injection framework for automatic instrumentation and full feature set.","Currently focused on Android and Kotlin Multiplatform apps; other platforms are not supported."]

   After: ["Requires use of Koin dependency injection framework for automatic instrumentation and full observability capabilities."]

   platforms

   Before: ["Supports Android and Kotlin Multiplatform apps including iOS targets."]

   After: ["Android and Kotlin Multiplatform including iOS targets."]

   summary

   Before: "Kotzilla is a developer observability platform for Android and Kotlin Multiplatform apps that detects production issues, diagnoses root causes, and applies accurate fixes using AI integration. It leverages Koin dependency injection to capture runtime data automatically without manual instrumentation, providing deep insights beyond traditional tools like Firebase."

   After: "Kotzilla is a developer observability platform designed for Android and Kotlin Multiplatform apps that integrates AI assistants to detect production issues, diagnose root causes, and apply accurate fixes. It leverages Koin's dependency injection framework to provide deep runtime data, architecture visibility, and fix patterns for efficient issue remediation without manual instrumentation."

   useCases

   Before: ["Detecting and diagnosing production crashes and performance issues in Android and Kotlin Multiplatform apps.","Accelerating issue resolution and reducing downtime by providing accurate fixes and deep app performance insights."]

   After: ["Detecting and diagnosing crashes, ANRs, slow startups, and performance issues in Android and Kotlin Multiplatform apps.","Applying accurate fixes to production issues using AI assistants connected through the MCP Server and validating fixes with runtime monitoring."]

   walkthrough

   Before: ["Step 1: Automatic issue detection of crashes, ANRs, slow startups, and performance issues.","Step 3: Validate fixes and monitor runtime data to alert on regressions."]

   After: ["Step 1: Automatic issue detection of crashes, ANRs, slow startups, and performance issues in apps.","Step 2: AI assistant uses the MCP Server to find root causes and apply accurate fixes.","Step 3: Validate fixes and monitor runtime data to alert on regressions."]