Crash Instrumentation

Organization

nexus-labs-automation

crash-instrumentation

Set up crash instrumentation with actionable context. Use when configuring crash capture, error boundaries, or breadcrumb strategies.

Overview

Publisher	nexus-labs-automation
Repository	`mobile-observability`
Skill name	`crash-instrumentation`
Stars	116
Forks	12
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 nexus-labs-automation on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/nexus-labs-automation/mobile-observability/tree/main/skills/crash-instrumentation

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/nexus-labs-automation/mobile-observability.git /tmp/mobile-observability
mkdir -p .claude/skills
cp -r /tmp/mobile-observability/skills/crash-instrumentation .claude/skills/crash-instrumentation

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Crash Instrumentation 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 Instrumentation 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 Instrumentation 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 Instrumentation

Capture crashes with the context needed to debug them.

Core Principle

A crash report without context is useless. Every crash should include:

Context	Why	Example
`screen`	Where it happened	"CheckoutScreen"
`job_name`	What user was doing	"checkout"
`job_step`	Where in the flow	"payment"
`breadcrumbs`	What led here	Last 20 user actions
`app_version`	Release correlation	"1.2.3"
`user_segment`	Who's affected	"premium", "trial"

Breadcrumb Strategy

Breadcrumbs are the trail leading to a crash. Capture:

Category	What to Log	Example
`navigation`	Screen transitions	"HomeScreen → CartScreen"
`user`	Taps, inputs, gestures	"Tapped checkout button"
`network`	API calls (not payloads)	"POST /api/orders started"
`state`	Key state changes	"Cart updated: 3 items"
`error`	Non-fatal errors	"Retry #2 for payment"

Limit: Keep last 20-50 breadcrumbs. More is noise.

Error Boundaries

Catch errors before they crash the app:

swift
// iOS - capture context before crash
func captureError(_ error: Error, screen: String, job: String?) {
    Observability.captureError(error, context: [
        "screen": screen,
        "job_name": job ?? "unknown",
        "session_duration": sessionDuration(),
        "memory_pressure": memoryPressure()
    ])
}

kotlin
// Android - uncaught exception handler
Thread.setDefaultUncaughtExceptionHandler { thread, throwable ->
    Observability.captureError(throwable, mapOf(
        "thread" to thread.name,
        "screen" to currentScreen,
        "job_name" to currentJob
    ))
    previousHandler?.uncaughtException(thread, throwable)
}

What NOT to Attach

Don't	Why
Full stack traces in breadcrumbs	Redundant, SDK captures this
User input text	PII risk
Full request/response bodies	Size limits, PII
Entire app state	Unbounded, noise

Crash Types to Handle

Platform	Type	Instrumentation
iOS	`EXC_BAD_ACCESS`	Breadcrumbs, memory context
iOS	`SIGKILL` (watchdog)	Background task tracking
Android	`ANR`	Main thread breadcrumbs
Android	`OutOfMemoryError`	Memory tracking
React Native	JS exceptions	Error boundaries

Implementation

See references/crash-reporting.md for:

Platform-specific crash capture setup
Breadcrumb implementation patterns
Vendor SDK configuration

See skills/symbolication-setup for readable stack traces.

Frequently asked questions

What does the Crash Instrumentation AI skill do?

Set up crash instrumentation with actionable context. Use when configuring crash capture, error boundaries, or breadcrumb strategies.

Why use Crash Instrumentation on TypingMind?

Because you install it once and use it with any model. Crash Instrumentation 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 Instrumentation in TypingMind?

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

Which AI models can use Crash Instrumentation?

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 Instrumentation?

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

Is the Crash Instrumentation AI skill free?

Yes. It is published on GitHub by nexus-labs-automation 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Crash Instrumentation

Core Principle

Breadcrumb Strategy

Error Boundaries

What NOT to Attach

Crash Types to Handle

Implementation

Frequently asked questions

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