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/understudy-ai/understudy/weathernpx skills add understudy-ai/understudy --skill weathergit clone --depth 1 https://github.com/understudy-ai/understudyWhat 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 | $0.00055 | $0.00662 |
| Opus 5 | $0.00028 | $0.00331 |
| Sonnet 5 | $0.00011 | $0.00132 |
| Haiku 4.5 | $0.00006 | $0.00066 |
Grade A, and why
weather 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 3d 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.
metadata: { "understudy": { "emoji": "🌤️", "requires": { "bins": ["curl"] } } } This is a copy
97% identical to weather — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Weather Skill
Get current weather conditions and forecasts.
When to Use
✅ USE this skill when:
- "What's the weather?"
- "Will it rain today/tomorrow?"
- "Temperature in [city]"
- "Weather forecast for the week"
- Travel planning weather checks
When NOT to Use
❌ DON'T use this skill when:
- Historical weather data → use weather archives/APIs
- Climate analysis or trends → use specialized data sources
- Hyper-local microclimate data → use local sensors
- Severe weather alerts → check official NWS sources
- Aviation/marine weather → use specialized services (METAR, etc.)
Location
Always include a city, region, or airport code in weather queries.
Commands
Current Weather
# One-line summary
curl "wttr.in/London?format=3"
# Detailed current conditions
curl "wttr.in/London?0"
# Specific city
curl "wttr.in/New+York?format=3"
Forecasts
# 3-day forecast
curl "wttr.in/London"
# Week forecast
curl "wttr.in/London?format=v2"
# Specific day (0=today, 1=tomorrow, 2=day after)
curl "wttr.in/London?1"
Format Options
# One-liner
curl "wttr.in/London?format=%l:+%c+%t+%w"
# JSON output
curl "wttr.in/London?format=j1"
# PNG image
curl "wttr.in/London.png"
Format Codes
%c— Weather condition emoji%t— Temperature%f— "Feels like"%w— Wind%h— Humidity%p— Precipitation%l— Location
Quick Responses
"What's the weather?"
curl -s "wttr.in/London?format=%l:+%c+%t+(feels+like+%f),+%w+wind,+%h+humidity"
"Will it rain?"
curl -s "wttr.in/London?format=%l:+%c+%p"
"Weekend forecast"
curl "wttr.in/London?format=v2"
Notes
- No API key needed (uses wttr.in)
- Rate limited; don't spam requests
- Works for most global cities
- Supports airport codes:
curl wttr.in/ORD
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.
- 3d ago First seen · 113 lines · 55 tokens per session scan A c77dd5784214
weather is a skill published in the GitHub repository understudy-ai/understudy (456 stars, last pushed 2mo ago), licensed MIT. It adds 55 tokens to every session and 662 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 97% identical to weather, differing in 6 lines, and is treated as a copy.
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