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 ellmos-ai/skills --skill wettergit clone --depth 1 https://github.com/ellmos-ai/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/ellmos-ai/skills/wetter)<a href="https://agentmods.dev/skills/ellmos-ai/skills/wetter"><img src="https://agentmods.dev/badge/skills/ellmos-ai/skills/wetter/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/ellmos-ai/skills/wetter"><img src="https://agentmods.dev/badge/skills/ellmos-ai/skills/wetter.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 | $0.00043 | $0.00941 |
| Opus 5 | $0.00022 | $0.00470 |
| Sonnet 5 | $0.00009 | $0.00188 |
| Haiku 4.5 | $0.00004 | $0.00094 |
Grade A, and why
wetter 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 11d 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.
dependencies: {'tools': ['wetter_core.py'], 'services': [], 'protocols': [], 'python': ['urllib', 'json']} How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wetter
Schnelle, schluesselfreie Wetterauskunft fuer den Alltag.
Zweck
Beantwortet „Wie wird das Wetter?"-Fragen ohne API-Key (Datenquelle: wttr.in).
Liefert aktuelles Wetter (Temperatur, gefuehlt, Wind, Luftfeuchte, UV) plus eine
kompakte 3-Tage-Vorschau. Userneutral: kein fester Standort im Code — der Ort
kommt aus der Anfrage oder aus assist/prefs.json (wetter_default_location),
die das LLM interaktiv mit dem Nutzer fuellt.
Trigger
| Nutzereingabe | Aktion |
|---|---|
| „Wetter fuer Potsdam?" / „Wie wird das Wetter in Hamburg?" | wetter_core.py "<Ort>" |
| „Wetter morgen?" (ohne Ort) | wetter_core.py --default (Ort aus prefs) |
| „Mein Standard-Wetterort ist Potsdam" | wetter_core.py --set-default "Potsdam" |
| Koordinaten bekannt | wetter_core.py <lat> <lon> |
Workflow
1. Ort bestimmen: aus Anfrage; sonst prefs.json (wetter_default_location);
sonst Nutzer interaktiv fragen + optional als Default speichern.
2. wetter_core.py abfragen (wttr.in, 2 Versuche, 30-min-Cache).
3. Lesbaren Wetter-Text + 3-Tage-Vorschau praesentieren.
CLI-Einstieg (wetter_core.py)
python wetter_core.py "Potsdam" # Ort
python wetter_core.py 52.6789 13.5878 # Koordinaten
python wetter_core.py --default # Ort aus prefs.json
python wetter_core.py --set-default "Potsdam"
Store (optional)
- Kein Pflicht-Store. Optionaler Kurz-Cache
assist/wetter/.cache.json(TTL 30 min, best-effort) — vermeidet wiederholte Netzabrufe. - Standortpraeferenz in
assist/prefs.json(wetter_default_location).
Haltung
Wir nutzen wttr.in als schluesselfreie Default-Quelle, sind aber offen fuer andere Wetter-Backends (z.B. DWD/OpenWeather), falls der Nutzer das wuenscht.
Datenschutz
- Nur der Ortsname/die Koordinaten gehen an wttr.in (noetig fuer die Abfrage).
- Keine Telemetrie, kein Konto. Cache + Praeferenz bleiben lokal.
Verwandte Ressourcen
assist/AGENTS.md— Umbrella-Routerassist/reiseroute/— nutzt Wetter ggf. fuer Reiseplanung (geplant)
What ships with it
8 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.
- 11d ago First seen · 90 lines · 43 tokens per session scan A 77159e7ab4dc
wetter is a skill published in the GitHub repository ellmos-ai/skills (4 stars, last pushed yesterday), licensed MIT. It adds 43 tokens to every session and 941 once invoked, about $0.0002 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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