Symbolication Setup logo

Symbolication Setup

Organization
nexus-labs-automation
symbolication-setup

Configure crash symbolication for readable stack traces. Use when setting up dSYMs (iOS), ProGuard/R8 mappings (Android), or source maps (React Native).

Overview

Publishernexus-labs-automation
Repositorymobile-observability
Skill namesymbolication-setup
Stars
116
Forks
12
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 nexus-labs-automation on GitHub. Read the source before you install it.

Installation

Install the Symbolication Setup 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/nexus-labs-automation/mobile-observability.git /tmp/mobile-observability
mkdir -p .claude/skills
cp -r /tmp/mobile-observability/skills/symbolication-setup .claude/skills/symbolication-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Symbolication Setup 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 Symbolication Setup 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 Symbolication Setup 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.

Symbolication Setup

Make crash stack traces readable instead of memory addresses or minified code.

Why It Matters

Without symbolication:

0x104a3b2c8 <redacted> + 123

With symbolication:

PaymentViewController.processPayment() line 47

Unsymbolicated crashes are useless for debugging.

Platform Setup

iOS (dSYMs)

Xcode Build Phase Script:

bash
# Add to Build Phases → New Run Script Phase
if [ "${CONFIGURATION}" = "Release" ]; then
    # Sentry
    sentry-cli upload-dif --include-sources "${DWARF_DSYM_FOLDER_PATH}"

    # Or Crashlytics
    "${PODS_ROOT}/FirebaseCrashlytics/upload-symbols" \
        -gsp "${PROJECT_DIR}/GoogleService-Info.plist" \
        -p ios "${DWARF_DSYM_FOLDER_PATH}"
fi

Find missing dSYMs:

bash
# Recent archives
find ~/Library/Developer/Xcode/Archives -name "*.dSYM" -mtime -7

# Verify UUID matches
dwarfdump --uuid MyApp.app.dSYM

Android (ProGuard/R8)

build.gradle.kts:

kotlin
android {
    buildTypes {
        release {
            isMinifyEnabled = true
            proguardFiles(
                getDefaultProguardFile("proguard-android-optimize.txt"),
                "proguard-rules.pro"
            )
        }
    }
}

// Sentry auto-upload
sentry {
    autoUploadProguardMapping.set(true)
    uploadNativeSymbols.set(true)
}

// Or manual upload in CI
// sentry-cli upload-proguard --android-manifest app/build/.../AndroidManifest.xml mapping.txt

Keep rules for crash reporting:

proguard
# proguard-rules.pro
-keepattributes SourceFile,LineNumberTable
-renamesourcefileattribute SourceFile

# Keep Sentry classes
-keep class io.sentry.** { *; }

React Native (Source Maps)

Expo (app.json):

json
{
  "expo": {
    "plugins": [
      ["@sentry/react-native/expo", {
        "organization": "your-org",
        "project": "your-project"
      }]
    ],
    "hooks": {
      "postPublish": [{
        "file": "sentry-expo/upload-sourcemaps"
      }]
    }
  }
}

Bare React Native (CI):

bash
# After build
sentry-cli releases files $VERSION upload-sourcemaps \
    --dist $BUILD_NUMBER \
    ./build/sourcemaps

Hermes bytecode:

bash
# Hermes requires source maps - verify with:
sentry-cli sourcemaps explain <event-id>

Verification Checklist

  • Release builds upload symbols automatically
  • CI pipeline includes symbol upload step
  • Test crash shows readable stack trace
  • Source maps include original source (not just line numbers)
  • Build numbers match between app and uploaded symbols

Common Issues

SymptomCauseFix
<redacted> in stackMissing dSYMUpload dSYM for that build
Line numbers wrongSource map mismatchVerify release/dist strings match
Only framework symbolsApp dSYM missingCheck archive includes app dSYM
<unknown> in RNHermes without source mapsConfigure Hermes source map generation

Vendor Commands

VendorVerify Upload
Sentrysentry-cli debug-files check <UUID>
CrashlyticsFirebase Console → Crashlytics → Missing dSYMs
Bugsnagbugsnag-cli upload with --dry-run
DatadogDashboard → Error Tracking → Symbol Files
bitdriftDashboard or CLI for dSYM, Gradle plugin for ProGuard
New ReliciOS dSYM via build script or newrelic-cli; Android ProGuard auto-uploaded by NR Gradle plugin

Related Skills

  • See skills/crash-instrumentation for breadcrumb strategies and crash context
  • Symbolication is Tier 1 in skills/instrumentation-planning

Frequently asked questions

What does the Symbolication Setup AI skill do?

Configure crash symbolication for readable stack traces. Use when setting up dSYMs (iOS), ProGuard/R8 mappings (Android), or source maps (React Native).

Why use Symbolication Setup on TypingMind?

Because you install it once and use it with any model. Symbolication Setup 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 Symbolication Setup in TypingMind?

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

Which AI models can use Symbolication Setup?

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 Symbolication Setup?

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

Is the Symbolication Setup 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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