I built a coding agent that works with 8k context local models
Beats Aider for local models by mapping codebases into static Markdown files.

Answers the real EV question: can I get there and back? 700 models, live charger data, no monetization trap.
EV owners planning trips, especially in under-charted regions; fleet managers
Google Maps EV routing · A Better Route Planner · Plugshare
You pick your car, drop a start pin, set your current charge %, and hit Compute Reach. You get two circles — outer for one-way range, inner for round-trip — plus all charging stations within reach as pins. Click any pin to open navigation in Google Maps.
Stack: vanilla JS + Leaflet, no build step, hosted on Vercel. Charger data merges OpenChargeMap and OpenStreetMap Overpass with deduplication. 700+ EV presets across 20+ markets (US, EU, India, China, AU, etc.) synced every 12h via a Python pipeline on GitHub Actions.
The catalog pipeline ingests fueleconomy.gov, afdc.energy.gov, cardekho.com, and greenvehicleguide.gov.au, plus region-native seed files. It has anti-regression guardrails and a canary→stable promotion workflow so bad syncs don't silently ship.
https://ev-mapping.vercel.app Source: https://github.com/novelmartis/ev-mapping
Feedback welcome — especially on range accuracy and charger pin coverage in non-US markets.
Beats Aider for local models by mapping codebases into static Markdown files.
Google Maps is clunky, but this landing page offers zero proof of a better map engine.
LLM cost calculator with current pricing, but spreadsheets and existing tools already do this.
Tactile unit circle finally makes SOHCAHTOA click—but the App Store is crowded with ed apps.
PE exit math made interactive—rolling 30% at 6x then 3x beats 100% upfront cash.
Yet another token calculator when OpenAI and dozens of others already exist.