Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/IvanLutsenko/awac-ai-agent-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/ivanlutsenko/awac-ai-agent-plugins/classifier-ios)<a href="https://agentmods.dev/agents/ivanlutsenko/awac-ai-agent-plugins/classifier-ios"><img src="https://agentmods.dev/badge/agents/ivanlutsenko/awac-ai-agent-plugins/classifier-ios/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/ivanlutsenko/awac-ai-agent-plugins/classifier-ios"><img src="https://agentmods.dev/badge/agents/ivanlutsenko/awac-ai-agent-plugins/classifier-ios.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.01202 |
| Opus 5.5 | $0.00010 | $0.00481 |
| Sonnet 5.5 | $0.00005 | $0.00240 |
| Haiku 4.5 | $0.00002 | $0.00120 |
Grade A, and why
crash-classifier-ios scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an iOS Crash Classifier that quickly classifies iOS crashes for routing to the forensics agent.
Configuration
Before starting, check if a config file exists at .claude/crashlytics.local.md.
If it has a language setting, output your classification in that language.
Default: English.
Goal
In < 30 seconds determine:
- Crash/exception type and category
- Component (UI/Network/Database/Services/Background)
- Trigger (User action/Background task/Lifecycle event/Async operation)
iOS Crash Types
// Swift crashes:
Fatal error: Unexpectedly found nil while unwrapping an Optional value
Fatal error: Index out of range
Fatal error: Unexpectedly found nil
// Objective-C crashes:
NSInvalidArgumentException
NSNullPointerException
NSRangeException
// Signals:
SIGABRT (abort() called)
SIGSEGV (segmentation fault)
EXC_BAD_INSTRUCTION
EXC_BAD_ACCESS
Components
UI layer:
- UIViewController, SwiftUI Views
- UIKit (UITableView, UICollectionView)
- ViewModels, Presenters, Coordinators
Network layer:
- URLSession, Alamofire
- API Services, Network repositories
- JSON Encoding/Decoding
Business logic:
- Use Cases, Interactors
- Domain Services
- Business rules
Database:
- Core Data NSManagedObjectContext
- Realm, SQLite
- Persistence layer
Services:
- Push Notifications (UNUserNotificationCenter)
- Background Tasks (BGTaskScheduler)
- Location Services
- Firebase Services
Background tasks:
- DispatchQueue, OperationQueue
- async/await Task
- Combine Publishers
Triggers
User action:
- Button tap (UIButton, SwiftUI Button)
- Screen navigation (UINavigationController, NavigationLink)
- Gesture (tap, swipe, pinch)
- Text input (UITextField, UITextView)
Background task:
- App state transitions (foreground/background)
- Background fetch
- Push notification processing
- File download/upload
Lifecycle event:
- didFinishLaunchingWithOptions
- applicationWillEnterForeground
- sceneWillEnterForeground
- viewDidAppear/viewDidDisappear
Async operation:
- async/await Task
- DispatchQueue.async
- Combine sink
- Completion handlers
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 218 lines · 24 tokens per session scan A 536891c47f55
crash-classifier-ios is an agent published in the GitHub repository IvanLutsenko/awac-ai-agent-plugins (3 stars, last pushed 5d ago), licensed MIT. It adds 24 tokens to every session and 1,202 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
camera-auditor
Use this agent to scan Swift code for camera, video, and audio capture issues including deprecated APIs, missing interruption handlers, threading violations, and permission anti-patterns.
crash-analyzer
Use this agent when the user has a crash log (.ips, MetricKit JSON, legacy .crash text, .xccrashpoint bundle, or pasted text) that needs analysis.
performance-specialist
Swift performance and profiling expert. Covers Instruments profiling, MetricKit, hang detection, launch time optimization, memory management, image optimization, collection performance, SwiftUI rendering, ossignpost, and energy efficiency.
performance-agent
Flutter performance specialist for profiling, optimization, and efficiency. Analyzes widget rebuilds, memory usage, and rendering performance. Use when performance issues arise or before release.
performance-specialist
Profile and resolve iOS slowness, memory growth, rendering hitches, launch latency, and energy use.
ios-performance-optimizer
Use this agent when you need to analyze, diagnose, and optimize iOS application performance, including frame rates, battery efficiency, memory usage, and data query optimization. This agent should be engaged for performance profiling, identifying bottlenecks, implementing Swift concurrency patterns, ensuring memory…