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 yzxingtu2026/novusai-saas --skill weather_realtimegit clone --depth 1 https://github.com/yzxingtu2026/novusai-saasWrote 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/yzxingtu2026/novusai-saas/weather_realtime)<a href="https://agentmods.dev/skills/yzxingtu2026/novusai-saas/weather_realtime"><img src="https://agentmods.dev/badge/skills/yzxingtu2026/novusai-saas/weather_realtime/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/yzxingtu2026/novusai-saas/weather_realtime"><img src="https://agentmods.dev/badge/skills/yzxingtu2026/novusai-saas/weather_realtime.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 | $0.00030 | $0.00142 |
| Opus 5 | $0.00015 | $0.00071 |
| Sonnet 5 | $0.00006 | $0.00028 |
| Haiku 4.5 | $0.00003 | $0.00014 |
Grade A, and why
weather_realtime 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 12d 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
Weather Realtime Skill
This skill provides live weather lookup backed by the Weather Widget plugin.
Use it for:
- current weather in a city
- multi-day forecast
- temperature, humidity, wind speed, UV index, and condition checks
Do not use it for:
- historical climate analysis
- severe weather alerts that require official emergency feeds
- non-weather travel planning questions unless live weather is explicitly needed
References live under references/.
Examples live under examples/.
Implementation notes live under scripts/.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 23 lines · 30 tokens per session scan A b17ad9a1362f
weather_realtime is a skill published in the GitHub repository yzxingtu2026/novusai-saas (24 stars, last pushed yesterday), licensed MIT. It adds 30 tokens to every session and 142 once invoked, about $0.0002 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 2026-08-30.
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frontend-conventions
Frontend convention reference (SvelteKit / Svelte 5). Auto-injected into frontend-aware agents - not user-invocable.
address-review
Read PR review comments from GitHub, evaluate, address, and reply.