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Crash Analytics

CommunityPopular
Eronred
crash-analytics

When the user wants to monitor, triage, or reduce their app's crash rate — including setting up Crashlytics, prioritizing which crashes to fix first, interpreting crash data, and understanding how crashes affect App Store ranking. Use when the user mentions "crash", "crashlytics", "crash rate", "ANR", "app not responding", "crash-free sessions", "crash-free users", "symbolication", "stability", "firebase crashes", "app crashing", or "crash report". For overall analytics setup, see app-analytics.

Overview

PublisherEronred
Repositoryaso-skills
Skill namecrash-analytics
Stars
1.9K
Forks
116
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Eronred on GitHub. Read the source before you install it.

Installation

Install the Crash Analytics AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Eronred/aso-skills.git /tmp/aso-skills
mkdir -p .claude/skills
cp -r /tmp/aso-skills/skills/crash-analytics .claude/skills/crash-analytics
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Crash Analytics in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Crash Analytics on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Crash Analytics is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Crash Analytics

You help triage, prioritize, and reduce app crashes — and understand how crash rate affects App Store discoverability and ratings.

Why Crash Rate Is an ASO Signal

  • App Store ranking — Apple's algorithm penalizes apps with high crash rates
  • App Store featuring — High crash rate disqualifies editorial consideration
  • Ratings — Crashes are the #1 cause of 1-star reviews
  • Retention — A crash in the first session destroys Day 1 retention

Target: crash-free sessions > 99.5% | crash-free users > 99%

Tools

ToolWhat it providesSetup
Firebase CrashlyticsReal-time crashes, ANRs, symbolicated stack tracesAdd FirebaseCrashlytics pod/SPM package
App Store ConnectCrash rate trend, crashes per sessionBuilt-in, no code needed
Xcode OrganizerAggregated crash logs from TestFlight + App StoreXcode → Window → Organizer → Crashes
MetricKitOn-device diagnostics, hang rate, launch timeiOS 13+, automatic

Recommended: Crashlytics (real-time alerts + search) + App Store Connect (trend validation)

Crashlytics Setup

iOS (Swift)

swift
// AppDelegate or @main App struct
import FirebaseCore
import FirebaseCrashlytics

@main
struct MyApp: App {
    init() {
        FirebaseApp.configure()
        // Crashlytics is auto-initialized
    }
}

Non-fatal errors (track without crashing)

swift
// Log a non-fatal error
Crashlytics.crashlytics().record(error: error)

// Log a custom key for debugging context
Crashlytics.crashlytics().setCustomValue(userId, forKey: "user_id")
Crashlytics.crashlytics().setCustomValue(screenName, forKey: "current_screen")

Android (Kotlin)

kotlin
// build.gradle (app)
implementation("com.google.firebase:firebase-crashlytics:18.x.x")

// No additional code needed — auto-captures unhandled exceptions
// For non-fatal:
FirebaseCrashlytics.getInstance().recordException(throwable)

Triage Framework

Not all crashes are equal. Prioritize by impact:

Priority Score = Crash Frequency × Affected Users × User Segment Weight

PriorityCriteriaResponse time
P0 — CriticalCrashes on launch / checkout / core feature; >1% of sessionsFix today
P1 — HighCrashes in common flows; >0.1% of sessionsFix this release
P2 — MediumEdge case crashes; <0.1% of sessionsFix next release
P3 — LowRare, non-blocking crashes; <0.01% of sessionsBacklog

Crashlytics Dashboard Triage

  1. Sort by "Impact" (unique users affected), not frequency
  2. Group: onboarding, checkout, core feature, background, launch
  3. Assign P0/P1 to the top 3–5 issues
  4. Set a velocity alert in Crashlytics for any issue affecting >0.5% of users

Reading a Crash Report

Fatal Exception: com.example.NullPointerException
  at com.example.UserProfileVC.loadData:87
  at com.example.HomeVC.viewDidLoad:45

Keys:
  user_id: 12345
  current_screen: "home"
  app_version: "2.3.1"
  os_version: "iOS 17.3"

Steps to debug:

  1. Open the file and line in Xcode (UserProfileVC.swift:87)
  2. Check what can be nil at that point
  3. Reproduce with the user context (OS version, device, screen)
  4. Write a failing test before fixing

Symbolication

Crashlytics auto-symbolicates if you upload dSYMs. If you see unsymbolicated traces:

bash
# Manually upload dSYMs
./Pods/FirebaseCrashlytics/upload-symbols -gsp GoogleService-Info.plist -p ios MyApp.app.dSYM

For Bitcode-enabled builds, download dSYMs from App Store Connect → Activity → Build → dSYMs.

App Store Connect Crash Data

  • App Store Connect → App Analytics → Crashes — Crash rate trend per version
  • Compare crash rate before and after each release
  • A spike on a specific version = regression in that release

Crash rate formula: Crashes / Sessions × 100

Release Strategy to Minimize Blast Radius

Use phased releases to catch crashes before full rollout:

iOS: App Store Connect → Version → Phased Release (7-day rollout: 1% → 2% → 5% → 10% → 20% → 50% → 100%)

Android: Play Console → Production → Managed publishing → Rollout percentage

Rule: Monitor Crashlytics for 24 hours at each phase. If crash rate increases >0.2%, pause rollout.

Responding to Crash-Driven 1-Star Reviews

  1. Identify the app version where crash-related 1-stars appeared
  2. Fix the crash
  3. Reply to each crash-related review: "Fixed in version X.X — please update"
  4. After update ships, use rating-prompt-strategy to recover rating

Output Format

Crash Audit Report

Stability Report — [App Name] v[version] ([period])

Crash-free sessions: [X]%  (target: >99.5%)
Crash-free users:    [X]%  (target: >99%)
Top crash issues:

P0 Issues (fix immediately):
  #1 [Exception type] — [X] users, [X]% of sessions
     File: [filename:line]
     Cause: [hypothesis]
     Fix: [specific action]

P1 Issues (this release):
  #2 [Exception type] — [X] users, [X]% of sessions
     ...

Action Plan:
  Today:     Fix P0 issue #1 → release hotfix
  This week: Fix P1 issues #2, #3 → include in v[X.X]
  Monitoring: Set velocity alert at 0.5% session threshold

Related Skills

  • app-analytics — Full analytics stack; Crashlytics is one piece
  • rating-prompt-strategy — Recover rating after fixing crash-driven 1-stars
  • review-management — Respond to crash-related reviews
  • retention-optimization — Crashes on Day 1 destroy retention metrics
  • app-store-featured — Crash rate > 2% disqualifies editorial featuring

Frequently asked questions

What does the Crash Analytics AI skill do?

When the user wants to monitor, triage, or reduce their app's crash rate — including setting up Crashlytics, prioritizing which crashes to fix first, interpreting crash data, and understanding how crashes affect App Store ranking. Use when the user mentions "crash", "crashlytics", "crash rate", "ANR", "app not responding", "crash-free sessions", "crash-free users", "symbolication", "stability", "firebase crashes", "app crashing", or "crash report". For overall analytics setup, see app-analytics.

Why use Crash Analytics on TypingMind?

Because you install it once and use it with any model. Crash Analytics is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Crash Analytics in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Eronred/aso-skills/tree/main/skills/crash-analytics. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Crash Analytics?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Crash Analytics?

As many as you like. As long as a model supports skills, you can use Crash Analytics with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Crash Analytics AI skill free?

Yes. It is published on GitHub by Eronred under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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