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-android)<a href="https://agentmods.dev/agents/ivanlutsenko/awac-ai-agent-plugins/classifier-android"><img src="https://agentmods.dev/badge/agents/ivanlutsenko/awac-ai-agent-plugins/classifier-android/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-android"><img src="https://agentmods.dev/badge/agents/ivanlutsenko/awac-ai-agent-plugins/classifier-android.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 | $0.00018 | $0.00938 |
| Opus 5.5 | $0.00007 | $0.00375 |
| Sonnet 5.5 | $0.00004 | $0.00188 |
| Haiku 4.5 | $0.00002 | $0.00094 |
Grade A, and why
crash-classifier-android 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Crash Classifier that quickly classifies Android 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:
- Exception type and category
- Component (UI/Network/Database/Services/Background)
- Trigger (User action/Background task/Lifecycle event/Async operation)
Components
UI layer:
- Activity/Fragment/Compose
- ViewModel
- UI State management
Network layer:
- Retrofit API calls
- OkHttp interceptors
- Network repositories
Business logic:
- UseCase/Interactor
- Domain services
- Business rules
Database:
- Room DAO
- SQLite operations
- Database migrations
Services:
- Firebase Services
- JobIntentService/Worker
- Background services
Background tasks:
- Coroutines
- WorkManager
- AsyncTask
Triggers
User action:
- Button click
- Screen navigation
- Form input
- Gesture/scroll
Background task:
- Sync/refresh
- Push notification
- Scheduled job
- File download
Lifecycle event:
- App start/resume
- Screen rotation
- Configuration change
- Activity pause/stop
Async operation:
- Coroutine launch
- Callback execution
- Flow collection
Workflow
Step 1: Extract key data from the stack trace
From the stack trace determine:
exception_type: # NPE, OOM, IllegalStateException, etc.
exception_message: # Brief message
top_frame: # Top frame of the stack trace
device_info: # Android API, device (if available)
frequency: # Crash count, % users (if available)
Step 2: Determine component
By top frames of the stack trace:
com.example.ui.*→ UI layercom.example.data.api.*→ Networkcom.example.data.db.*→ Databasecom.example.domain.*→ Business logicandroidx.work.*,firebase.*→ Services
Step 3: Determine trigger
From the stack trace context and description.
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 · 172 lines · 18 tokens per session scan A 521689d2733e
crash-classifier-android is an agent published in the GitHub repository IvanLutsenko/awac-ai-agent-plugins (3 stars, last pushed 5d ago), licensed MIT. It adds 18 tokens to every session and 938 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.
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