Calculate line-of-sight and road distances between two cities using free OpenStreetMap services.
npx skills add https://github.com/besoeasy/open-skills --skill city-distance
Purpose: Calculate line-of-sight and road distances between two cities using free, API-keyless public services and local haversine calculations.
What it does:
Files:
When to use:
Prerequisites:
Agent prompt:
> Calculate both the straight-line (Haversine) distance and the driving distance between {cityA} and {cityB} using free OpenStreetMap services. Return distances in km and optionally list major towns along the driving route.
Examples
--------
Bash (uses OSM routing, jq):
set -euo pipefail
CITY_A_LAT=48.8566
CITY_A_LON=2.3522
CITY_B_LAT=52.52
CITY_B_LON=13.4050
URL="https://routing.openstreetmap.de/routed-car/route/v1/driving/${CITY_A_LON},${CITY_A_LAT};${CITY_B_LON},${CITY_B_LAT}?overview=false"
curl -fsS --max-time 10 "$URL" | jq -r '.routes[0].distance / 1000'
Node.js (uses native fetch, AbortController, error handling):
// city_distance_calculator.js
async function fetchJson(url, timeoutMs = 10000) {
const controller = new AbortController();
const id = setTimeout(() => controller.abort(), timeoutMs);
try {
const res = await fetch(url, { signal: controller.signal });
clearTimeout(id);
if (!res.ok) throw new Error(`HTTP ${res.status}`);
return await res.json();
} catch (err) {
clearTimeout(id);
throw err;
}
}
function haversine(lat1, lon1, lat2, lon2) {
const R = 6371e3;
const toRad = d => (d * Math.PI) / 180;
const φ1 = toRad(lat1), φ2 = toRad(lat2);
const Δφ = toRad(lat2 - lat1), Δλ = toRad(lon2 - lon1);
const a = Math.sin(Δφ/2)**2 + Math.cos(φ1)*Math.cos(φ2)*Math.sin(Δλ/2)**2;
const c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1 - a));
return (R * c) / 1000;
}
(async () => {
const paris = { lat: 48.8566, lon: 2.3522 };
const berlin = { lat: 52.52, lon: 13.4050 };
console.log('Line-of-sight (km):', haversine(paris.lat, paris.lon, berlin.lat, berlin.lon).toFixed(2));
const url = `https://routing.openstreetmap.de/routed-car/route/v1/driving/${paris.lon},${paris.lat};${berlin.lon},${berlin.lat}?overview=false`;
const data = await fetchJson(url, 15000);
console.log('Driving distance (km):', (data.routes[0].distance / 1000).toFixed(2));
})();
Notes / Rate limits:
See also:
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take besoeasy/city-distance from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.