GlideComp

GlideComp is a web application for analyzing hanggliding and paragliding competition flights.

What it does:

• Pilots (or competition organizers) load IGC track log files and XCTask task files in the browser
• The app analyzes flights: task completion, scoring explanations, glide performance, thermal/climb analysis
• Full CIVL GAP scoring implementation (FAI Sporting Code Section 7F) — distance, time, leading, and arrival points for both PG and HG
• Includes 2D (Mapbox) and 3D (Three.js globe) map visualization of flight tracks
• Competition management features: pilot registration, task setup, scoring, penalties, with a full audit log for transparency

How it's built:

• Client-side first — IGC parsing and flight analysis happen entirely in the browser, no server required for core functionality
• Frontend: TypeScript SPA hosted on Cloudflare Pages, using Basecoat UI components and Tailwind CSS
• Backend: Cloudflare Workers API for competition management, with D1 (SQLite) database and R2 storage
• Engine: A dedicated @glidecomp/engine package handles geo calculations (WGS84 ellipsoid math, Vincenty formulas) and flight analysis

Key design principles:

• No server-side storage needed for basic use — drag-and-drop files and analyze locally
• All scoring decisions are explainable and auditable
• Every mutation affecting competition scores is audit-logged

The app is live at glidecomp.com.

Features

• Flight event detection — automatic detection of takeoff, landing, thermals, glides, start/goal crossings, and turnpoint tagging
• Thermal analysis — entry/exit times, altitude gain, average climb rate
• Glide analysis — distance, altitude lost, L/D ratio, plus sink detection for poor glides
• GAP scoring — CIVL GAP scoring with distance, time, leading, and arrival points
• Competition management — create competitions, register pilots, upload IGC tracks, manage tasks, apply penalties, with full audit logging
• Authentication — Google OAuth login with user profiles
• Task editor — create and edit tasks with drag-to-reorder turnpoints, waypoint database search, and click-on-map placement
• Multiple data sources — drag & drop IGC/XCTSK files, import from XContest by task code, or import from AirScore by URL
• Interactive map — 2D (Mapbox/Leaflet) and 3D views with track overlay, task cylinders, and map annotations
• Altitude sparkline — clickable time-series chart linked to events and map position
• Theme editor — customizable UI themes with color and font controls, import/export support
• Configurable units & detection — speed, altitude, distance, climb rate units; adjustable thermal/glide detection thresholds

Web Development

Prerequisites

• Bun (also requires Node.js 20+)
• A MapBox access token (for the map). If your token has URL restrictions, ensure glidecomp.com and localhost:3000 are in the allowed URLs list.

Setup

bun install

# Copy .env.example and add your MapBox token
cp .env.example .env
# Edit .env and set VITE_MAPBOX_TOKEN=your_token_here

Running locally (Docker)

The easiest way to start everything. Only the frontend port is exposed:

docker compose up --build

To run multiple worktrees side-by-side, override the port:

PORT=3001 docker compose up --build

Running locally (native)

Start the frontend and all API workers together:

bun run dev

This starts three services:

• Frontend — Vite dev server at http://localhost:3000
• Auth API — authentication worker at http://localhost:8788
• Competition API — competition management worker at http://localhost:8789

The auth worker requires a .dev.vars file in web/workers/auth-api/ — see docs/auth.md for setup.

To start only the frontend (without any workers):

bun run dev:frontend

To use AirScore features, also start the AirScore API worker (http://localhost:8787) in a separate terminal:

bun run --filter airscore-api dev

The frontend automatically detects the local worker. If you'd rather skip the worker and use the production API instead:

VITE_AIRSCORE_URL=https://glidecomp.com/api/airscore bun run dev

Tests and type checking

bun run test             # Run unit tests (engine + airscore worker) and type check
bun run test:comp        # Run competition API tests
bun run test:all         # Run all unit tests
bun run test:e2e         # Run Playwright end-to-end tests
bun run typecheck        # Type check root project
bun run typecheck:all    # Type check everything (frontend + engine + workers)

Chrome MCP server set up

Read https://developer.chrome.com/blog/chrome-devtools-mcp-debug-your-browser-session

GlideComp MCP server

GlideComp exposes an MCP server at https://glidecomp.com/mcp so AI agents can manage competitions, tasks, pilots, tracks, and scores. See docs/mcp.md for setup and available tools.

Deployment

• Push to master → deploys to production
• Push to other branches → deploys to preview URL

bun run deploy           # Manual deploy to Cloudflare Pages
bun run deploy:worker    # Manual deploy AirScore API Worker
bun run deploy:comp      # Manual deploy Competition API Worker
bun run deploy:auth      # Manual deploy Auth API Worker
bun run deploy:all       # Deploy Pages + all Workers

URLs:

• Production: https://glidecomp.com
• Previews: https://{branch}.glidecomp.pages.dev

CLI Scripts

detect-events - Detect flight events from an IGC file, outputting CSV:

bun run detect-events -- <flight.igc> [task.xctsk]

# Example with sample data
bun run detect-events -- \
  web/frontend/public/data/tracks/2025-01-05-Tushar-Corryong.igc \
  web/frontend/public/data/tasks/buje.xctsk

get-xcontest-task - Download a task from XContest by code:

bun run get-xcontest-task -- face
bun run get-xcontest-task -- --file task.json

score-task - Score multiple pilots against a task using CIVL GAP (FAI Sporting Code Section 7F):

bun run score-task <task.xctsk> <igc-file-or-folder>... [options]

# Options:
#   --scoring <PG|HG>         Sport type (default: PG)
#   --nominal-distance <m>    Nominal distance in meters (default: 70% of task distance)
#   --nominal-goal <ratio>    Nominal goal ratio 0-1 (default: 0.2)
#   --nominal-time <s>        Nominal time in seconds (default: 5400)
#   --min-distance <m>        Minimum distance in meters (default: 5000)
#   --no-leading              Disable leading (departure) points
#   --no-arrival              Disable arrival points
#   --json                    Output as JSON

# Example: score Corryong Cup 2026 Task 1 (HG, no leading/arrival)
bun run score-task \
  web/engine/tests/fixtures/corryong-cup-2026-t1/task.xctsk \
  web/engine/tests/fixtures/corryong-cup-2026-t1/ \
  --scoring HG --no-leading --no-arrival \
  --nominal-distance 35000 --nominal-goal 0.3

Example output:

=== Task Scoring Results (CIVL GAP) ===

Task distance:    73.9 km
Pilots:           32 flying / 32 present
In goal:          12 (37.5%)
Best time:        1:37:43

Task Validity:    100.0%
Available Points: 1000 (dist: 486, time: 514, lead: 0, arr: 0)

   #  Pilot                            Dist        Time   Dist Pts   Time Pts   Lead Pts    Arr Pts    Total
------------------------------------------------------------------------------------------------------------
   1  Jon Durand                    73.9 km     1:37:43      485.6      514.4        0.0        0.0     1000
   2  Rohan Holtkamp                73.9 km     1:46:05      485.6      386.9        0.0        0.0      872
   3  Peter  Burkitt                73.9 km     1:49:00      485.6      358.8        0.0        0.0      844
  ...
  13  Rich Reinauer                 72.0 km           -      473.1        0.0        0.0        0.0      473
  ...
  29  Rennick Kerr                   5.0 km           -       32.9        0.0        0.0        0.0       33

Project Structure

web/
  frontend/              - Cloudflare Pages frontend (Vite + TypeScript)
  engine/                - Shared analysis library (IGC parsing, event detection, GAP scoring)
    cli/                 - CLI utilities (detect-events, get-xcontest-task, score-task)
  workers/
    auth-api/            - Authentication API (Cloudflare Worker + D1)
    competition-api/     - Competition management API (Cloudflare Worker + D1 + R2)
    mcp-api/             - MCP server for AI agents (Cloudflare Worker)
    airscore-api/        - AirScore caching proxy (Cloudflare Worker)
  scripts/               - Operational scripts (secrets, test emails)
e2e/                     - Playwright end-to-end tests
docs/                    - Feature and architecture specifications