nano-banana-pro-prompts-recommend-skill
AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
ArriveLah Singapore Bus Arrivals
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install abhayjb/buslah打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Natural language bus lookup for Singapore.
bus from <source location> to <destination location>
Examples:
Use web_fetch to resolve the source location to coordinates via OneMap API:
https://www.onemap.gov.sg/api/common/elastic/search?searchVal=<source>&returnGeom=Y&getAddrDetails=Y&pageNum=1
Extract LATITUDE and LONGITUDE from the first result.
Fetch the full Singapore bus stop list and find stops closest to source coordinates:
https://busrouter.sg/data/2/bus-stops.json
This returns a JSON object where each key is a bus stop code, with fields: description, road, lat, lng.
Compute distance using: sqrt((lat2-lat1)^2 + (lng2-lng1)^2) (approximate is fine for short distances).
Pick the 3 nearest stops within ~300m.
Same as Step 1 for the destination. Extract its coordinates.
For each of the 3 nearest source stops, fetch arrivals:
https://arrivelah2.busrouter.sg/?id=<stop_code>
Then for each bus service at those stops, check if it passes near the destination using:
https://busrouter.sg/data/2/routes.json
This maps bus service numbers to arrays of stop codes in order. Cross-reference with bus-stops.json to get coordinates of each stop on the route, and check if any stop is within ~400m of the destination coordinates.
Keep only buses that:
For each matching bus at the source stop, get from the arrivelah2 response:
next.duration_ms → minutes unti...这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# ArriveLah - Singapore Bus Arrivals Natural language bus lookup for Singapore. ## Trigger Format ``` bus from <source location> to <destination location> ``` Examples: - "bus from Silat Road Sikh Temple to Queens condo" - "bus from Tanjong Pagar MRT to VivoCity" - "bus from my office to home" ## Step-by-Step Workflow ### Step 1: Geocode source location Use web_fetch to resolve the source location to coordinates via OneMap API: ``` https://www.onemap.gov.sg/api/common/elastic/search?searchVal=<source>&returnGeom=Y&getAddrDetails=Y&pageNum=1 ``` Extract `LATITUDE` and `LONGITUDE` from the first result. ### Step 2: Find nearest bus stops to source Fetch the full Singapore bus stop list and find stops closest to source coordinates: ``` https://busrouter.sg/data/2/bus-stops.json ``` This returns a JSON object where each key is a bus stop code, with fields: `description`, `road`, `lat`, `lng`. Compute distance using: `sqrt((lat2-lat1)^2 + (lng2-lng1)^2)` (approximate is fine for short distances). Pick the **3 nearest** stops within ~300m. ### Step 3: Geocode destination location Same as Step 1 for the destination. Extract its coordinates. ### Step 4: Find which buses go from source stops toward destination For each of the 3 nearest source stops, fetch arrivals: ``` https://arrivelah2.busrouter.sg/?id=<stop_code> ``` Then for each bus service at those stops, check if it passes near the destination using: ``` https://busrouter.sg/data/2/routes.json ``` This maps bus service numbers to arrays of stop codes in order. Cross-reference with bus-stops.json to get coordinates of each stop on the route, and check if any stop is within ~400m of the destination coordinates. Keep only buses that: 1. Have the source stop **before** the destination stop in their route (correct direction) 2. Pass within ~400m of the destination ### Step 5: Fetch live arrival times For each matching bus at the source stop, get from the arrivelah2 response: - `next.duration_ms` → minutes unti...
AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
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