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 skills/dinglebear-ai/rtailscale/tailscalenpx skills add dinglebear-ai/rtailscale --skill tailscalegit clone --depth 1 https://github.com/dinglebear-ai/rtailscaleWrote 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/dinglebear-ai/rtailscale/tailscale)<a href="https://agentmods.dev/skills/dinglebear-ai/rtailscale/tailscale"><img src="https://agentmods.dev/badge/skills/dinglebear-ai/rtailscale/tailscale.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 | $0.00175 | $0.01897 |
| Opus 5 | $0.00088 | $0.00949 |
| Sonnet 5 | $0.00035 | $0.00379 |
| Haiku 4.5 | $0.00017 | $0.00190 |
Grade A, and why
tailscale scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl "https://api.tailscale.com/api/v2/tailnet/$TAILSCALE_TAILNET/devices" \ The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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 · 196 lines · 175 tokens per session scan A 218eff1c6485
tailscale is a skill published in the GitHub repository dinglebear-ai/rtailscale (5 stars, last pushed 9d ago), licensed AGPL-3.0. It adds 175 tokens to every session and 1,897 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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