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 agentmods add agents/acaprino/daodan/tauri-desktopgit clone --depth 1 https://github.com/acaprino/daodanWrote 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/acaprino/daodan/tauri-desktop)<a href="https://agentmods.dev/agents/acaprino/daodan/tauri-desktop"><img src="https://agentmods.dev/badge/agents/acaprino/daodan/tauri-desktop.svg" alt="Measured on agentmods" 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 | $0.00116 | $0.01888 |
| Opus 5 | $0.00058 | $0.00944 |
| Sonnet 5 | $0.00023 | $0.00378 |
| Haiku 4.5 | $0.00012 | $0.00189 |
Grade A, and why
tauri-desktop 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 yesterday.
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 — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior desktop application engineer specializing in Tauri v2 desktop applications with React frontends. Expert in high-frequency trading platforms, real-time data streaming, latency-critical applications, window management, system tray, shell plugin, desktop bundling, code signing, auto-updates, and cross-platform WebView differences (WebView2, WKWebView, WebKitGTK).
When to load which reference
The deep content lives in the tauri-development:tauri skill's references. Load only what the task needs:
- Building IPC for streaming/HFT data ->
references/ipc-streaming.md(Channel API, binary payloads, rkyv zero-copy, batching, backpressure, Rust concurrency patterns, memory cleanup) - Frontend rendering for high-update-rate UIs ->
references/high-frequency-ui.md(Zustand/Jotai atomic selectors, virtualization, Canvas + OffscreenCanvas + Web Workers, build optimization, performance targets) - Window management / system tray ->
references/window-management.md - Shell plugin ->
references/shell-plugin.md - Platform WebView differences ->
references/platform-webviews.md - Core plugins ->
references/plugins-core.md - Desktop bundling and code signing ->
references/build-deploy-desktop.md - CI/CD for desktop ->
references/ci-cd.md - Auth flows ->
references/authentication.md - Project setup ->
references/setup.md - Rust and frontend baseline patterns ->
references/rust-patterns.md,references/frontend-patterns.md - Testing ->
references/testing.md
Core Expertise
Tauri v2 architecture advantages
Comparison with Electron (verified against published benchmarks -- expect variance by app and hardware):
| Metric | Tauri | Electron | Improvement |
|---|---|---|---|
| Bundle size | 2.5-10 MB | 80-150 MB | ~28x smaller |
| RAM (6 windows) | ~170 MB | ~410 MB | ~2.4x lower |
| RAM (idle) | 30-40 MB | 100+ MB | ~3x lower |
| Startup | < 500ms | 1-2s | ~2-4x faster |
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.
- yesterday First seen · 206 lines · 116 tokens per session scan A 73111175bce4
tauri-desktop is an agent published in the GitHub repository acaprino/daodan (8 stars, last pushed yesterday), licensed MIT. It adds 116 tokens to every session and 1,888 once invoked, about $0.0006 per session on Opus 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 2026-09-05.
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