AuC is a Python framework for running a single AI agent with an asynchronous, pluggable reasoning loop, language-model adapters, permission levels, and observable events. It is used to build coding and conversational agents with tools, security checks, web interfaces, background jobs, evaluations, and isolated execution. The catalogue entries are skills for extending its agent workflow.
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.
npx skills add ufy2024/AuC --skill android-clean-architecturegit clone --depth 1 https://github.com/ufy2024/AuCWrote 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/skills/ufy2024/auc/android-clean-architecture)<a href="https://agentmods.dev/skills/ufy2024/auc/android-clean-architecture"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/android-clean-architecture/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/skills/ufy2024/auc/android-clean-architecture"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/android-clean-architecture.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 20 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Data Exfiltration · line 248 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00034 | $0.02091 |
| Opus 5.5 | $0.00014 | $0.00836 |
| Sonnet 5.5 | $0.00007 | $0.00418 |
| Haiku 4.5 | $0.00003 | $0.00209 |
Grade A, and why
android-clean-architecture 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.
This is a copy
91% identical to android-clean-architecture — 26 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 360 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Android Clean Architecture
Clean Architecture patterns for Android and KMP projects. Covers module boundaries, dependency inversion, UseCase/Repository patterns, and data layer design with Room, SQLDelight, and Ktor.
When to Activate
- Structuring Android or KMP project modules
- Implementing UseCases, Repositories, or DataSources
- Designing data flow between layers (domain, data, presentation)
- Setting up dependency injection with Koin or Hilt
- Working with Room, SQLDelight, or Ktor in a layered architecture
Module Structure
Recommended Layout
project/
├── app/ # Android entry point, DI wiring, Application class
├── core/ # Shared utilities, base classes, error types
├── domain/ # UseCases, domain models, repository interfaces (pure Kotlin)
├── data/ # Repository implementations, DataSources, DB, network
├── presentation/ # Screens, ViewModels, UI models, navigation
├── design-system/ # Reusable Compose components, theme, typography
└── feature/ # Feature modules (optional, for larger projects)
├── auth/
├── settings/
└── profile/
Dependency Rules
app → presentation, domain, data, core
presentation → domain, design-system, core
data → domain, core
domain → core (or no dependencies)
core → (nothing)
Critical: domain must NEVER depend on data, presentation, or any framework. It contains pure Kotlin only.
Domain Layer
UseCase Pattern
Each UseCase represents one business operation. Use operator fun invoke for clean call sites:
class GetItemsByCategoryUseCase(
private val repository: ItemRepository
) {
suspend operator fun invoke(category: String): Result<List<Item>> {
return repository.getItemsByCategory(category)
}
}
// Flow-based UseCase for reactive streams
class ObserveUserProgressUseCase(
private val repository: UserRepository
) {
operator fun invoke(userId: String): Flow<UserProgress> {
return repository.observeProgress(userId)
}
}
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 · 360 lines · 34 tokens per session scan A 9322ee41c588
android-clean-architecture is a skill published in the GitHub repository ufy2024/AuC (1,073 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 2,091 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to android-clean-architecture, differing in 26 lines, and is treated as a copy.
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