Borrowing it
Nothing to install: this file belongs to zhouguoqing/QianYuan.AIAgenticFramework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zhouguoqing/QianYuan.AIAgenticFramework/main/.agents/skills/weather-query/SKILL.mdgit clone --depth 1 https://github.com/zhouguoqing/QianYuan.AIAgenticFrameworkWrote 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/zhouguoqing/qianyuan.aiagenticframework/weather-query)<a href="https://agentmods.dev/skills/zhouguoqing/qianyuan.aiagenticframework/weather-query"><img src="https://agentmods.dev/badge/skills/zhouguoqing/qianyuan.aiagenticframework/weather-query/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/zhouguoqing/qianyuan.aiagenticframework/weather-query"><img src="https://agentmods.dev/badge/skills/zhouguoqing/qianyuan.aiagenticframework/weather-query.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 | $0.00046 | $0.01925 |
| Opus 5 | $0.00023 | $0.00962 |
| Sonnet 5 | $0.00009 | $0.00385 |
| Haiku 4.5 | $0.00005 | $0.00193 |
Grade A, and why
weather-query 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.
response = requests.get(url, params={'query': query}) This is a copy
100% identical to weather-query — 0 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.
How it starts
The opening of the file, as written. The whole thing — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weather Query Skill
This skill enables AI agents to fetch real-time weather information and forecasts for locations in China using the 60s API.
When to Use This Skill
Use this skill when users:
- Ask about current weather conditions
- Want weather forecasts
- Need temperature, humidity, wind information
- Request air quality data
- Plan outdoor activities and need weather info
API Endpoints
1. Real-time Weather
URL: https://60s.viki.moe/v2/weather/realtime
Method: GET
2. Weather Forecast
URL: https://60s.viki.moe/v2/weather/forecast
Method: GET
Parameters
query(required): Location name in Chinese- Can be city name: "北京", "上海", "广州"
- Can be district name: "海淀区", "浦东新区"
How to Use
Get Real-time Weather
import requests
def get_realtime_weather(query):
url = 'https://60s.viki.moe/v2/weather/realtime'
response = requests.get(url, params={'query': query})
return response.json()
# Example
weather = get_realtime_weather('北京')
print(f"☁️ {weather['location']}天气")
print(f"🌡️ 温度:{weather['temperature']}°C")
print(f"💨 风速:{weather['wind']}")
print(f"💧 湿度:{weather['humidity']}")
Get Weather Forecast
def get_weather_forecast(query):
url = 'https://60s.viki.moe/v2/weather/forecast'
response = requests.get(url, params={'query': query})
return response.json()
# Example
forecast = get_weather_forecast('上海')
for day in forecast['forecast']:
print(f"{day['date']}: {day['weather']} {day['temp_low']}°C ~ {day['temp_high']}°C")
Simple bash example
# Real-time weather
curl "https://60s.viki.moe/v2/weather/realtime?query=北京"
# Weather forecast
curl "https://60s.viki.moe/v2/weather/forecast?query=上海"
Response Format
Real-time Weather Response
{
"location": "北京",
"weather": "晴",
"temperature": "15",
"humidity": "45%",
"wind": "东北风3级",
"air_quality": "良",
"updated": "2024-01-15 14:00:00"
}
Forecast Response
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 · 269 lines · 46 tokens per session scan A 603415296ae4
weather-query is a skill published in the GitHub repository zhouguoqing/QianYuan.AIAgenticFramework (36 stars, last pushed 25d ago), licensed Apache-2.0. It adds 46 tokens to every session and 1,925 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to weather-query, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
git-checkpoint
Use git as a safety net - create a checkpoint commit before risky or large changes and roll back cleanly if a change makes things worse. Use before multi-file refactors.
synthesize-report
Produces a citation-grounded summary across one or more workspace source files for summaries, briefings, literature reviews, or comparisons.
data-analysis
Statistical data analysis skill — use when the user asks to analyze numbers, compute statistics, or summarize datasets.
summarizer
Use when the user asks for a summary, TL;DR, or condensed version of any content.
research-repository
Build a repository that makes findings findable, reusable, and cumulative across teams. Use when the same research keeps getting redone. For synthesising one study, use affinity-diagram.
design-negotiation
Advocate for design quality, scope, and timeline with partners and leadership using evidence and shared goals. Use in the conversation itself. For the commercial vocabulary behind it, use business-design (ux-strategy).