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 prasad-vennam/Awesome-Android-AI-Agent-Skills --skill android-gemini-nanogit clone --depth 1 https://github.com/prasad-vennam/Awesome-Android-AI-Agent-SkillsWrote 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/prasad-vennam/awesome-android-ai-agent-skills/android-gemini-nano)<a href="https://agentmods.dev/skills/prasad-vennam/awesome-android-ai-agent-skills/android-gemini-nano"><img src="https://agentmods.dev/badge/skills/prasad-vennam/awesome-android-ai-agent-skills/android-gemini-nano/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/prasad-vennam/awesome-android-ai-agent-skills/android-gemini-nano"><img src="https://agentmods.dev/badge/skills/prasad-vennam/awesome-android-ai-agent-skills/android-gemini-nano.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 | $0.00022 | $0.00484 |
| Opus 5.5 | $0.00009 | $0.00194 |
| Sonnet 5.5 | $0.00004 | $0.00097 |
| Haiku 4.5 | $0.00002 | $0.00048 |
Grade A, and why
android-gemini-nano 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 2mo 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.
What it actually says
Android Gemini Nano On-Device Integration 🧠
Gemini Nano allows for powerful, completely on-device AI generation. Because it runs locally via the AICore Android system service, careful life-cycle and asynchronous resource management is required.
⚡ When to Use
- When building chat interfaces, generating summaries, or drafting text without cloud latency.
- When the user asks to integrate "Gemini Nano" or "AICore".
🏗️ Core Rules / Pillars
1. AICore Dependency and Availability Check
- Pattern: AICore might not be downloaded or fully initialized. Always check availability before starting a session.
- Implementation:
val generativeModel = GenerativeModel("gemini-nano") // ALWAYS verify availability first val isAvailable = generativeModel.isAvailable() if (!isAvailable) { // Request download or show fallback UI }
2. Streaming Responses with Flow
- Pattern: Because generation can take time on low-end devices, always use
generateContentStreamto stream the UI update instead of waiting for the full response. - Anti-Pattern: NEVER block the main thread.
- Implementation:
viewModelScope.launch { generativeModel.generateContentStream(prompt) .catch { e -> handleError(e) } .collect { chunk -> _uiState.update { it.copy(text = it.text + chunk.text) } } }
🚧 Critical Anti-Hallucination Guards
- Trap:
GenerativeModelis part of thecom.google.ai.client.generativeaiSDK. Do NOT hallucinate customAICoreManagerwrapper singletons.
🔗 Related Resources
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.
- 2mo ago First seen · 60 lines · 22 tokens per session scan A 98ac788146c8
android-gemini-nano is a skill published in the GitHub repository prasad-vennam/Awesome-Android-AI-Agent-Skills (11 stars, last pushed 7mo ago), licensed MIT. It adds 22 tokens to every session and 484 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.
android-gemini-nano compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| android-gemini-nanoprasad-vennam/Awesome-Android-AI-Agent-Skills | Skill | 11 | 7mo ago | MIT | A | 22 | Claude Code, Codex |
| ml-kit-genai-prompt-apiandroid/skills | Skill | 10k | yesterday | Apache-2.0 | A | 57 | Claude Code |
| model-authoringapple/coreai-models | Skill | 2.3k | yesterday | BSD-3-Clause | A | 95 | Claude Code |
| working-with-coreaiapple/coreai-models | Skill | 2.3k | yesterday | BSD-3-Clause | A | 91 | Claude Code |
| litert-runtimeandroid/skills | Skill | 10k | yesterday | Apache-2.0 | A | 150 | Claude Code |
| open-ontologiesfabio-rovai/open-ontologies | Skill | 2.8k | 2d ago | MIT | A | 109 | Claude Code |
| foundation-models-on-devicehashgraph-online/awesome-codex-plugins | Skill | 1.5k | yesterday | Apache-2.0 | A | 38 | Claude Code, Codex |