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 commands/netmindai-open/narranexus/deep_link.rsgit clone --depth 1 https://github.com/NetMindAI-Open/NarraNexusWrote 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/commands/netmindai-open/narranexus/deep_link.rs)<a href="https://agentmods.dev/commands/netmindai-open/narranexus/deep_link.rs"><img src="https://agentmods.dev/badge/commands/netmindai-open/narranexus/deep_link.rs.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 | $0.00000 | $0.00293 |
| Opus 5 | $0.00000 | $0.00147 |
| Sonnet 5 | $0.00000 | $0.00059 |
| Haiku 4.5 | $0.00000 | $0.00029 |
Grade A, and why
deep_link.rs 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 4d 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
commands/deep_link.rs — cold-start URL drain
Single #[tauri::command] consume_pending_deep_link that returns and
clears AppState::pending_deep_link. Frontend calls it once on App
mount via the wrapper in frontend/src/lib/tauri.ts::consumePendingDeepLink.
Why exists
Tauri's event channel does not queue events for not-yet-attached listeners.
A narranexus://install?... URL the OS hands us at cold start fires
on_open_url inside lib.rs::setup long before React renders and
attaches its deep-link-received listener — those events are silently
lost. The on_open_url callback therefore writes the URL into
AppState::pending_deep_link; the frontend's mount-time consume_*
call returns and clears it (single-shot — take()). Hot URLs (app
already running) take the event channel as usual.
Why command, not a static getter
#[tauri::command] ensures the IPC bridge handles capability checks
(deep-link plugin perms granted in capabilities/default.json) and
serialization automatically. The frontend just does
invoke('consume_pending_deep_link').
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.
- 4d ago First seen · 30 lines · 0 tokens per session scan A f9ca6872278b
deep_link.rs is a command published in the GitHub repository NetMindAI-Open/NarraNexus (85 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 293 tokens. 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 2026-08-30.
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