Roadtrip Navigator

RoadTrip Navigator

Turn "start + days" or "an existing route" into a road trip you can actually drive: paced into days, with overnight stops, fuel/charging, park reservations, seasonal road risks, and a map-first single-file HTML page.

North American road trips revolve around the car, not flights: how many hours do we drive today, where do we sleep, will we make it on the fuel/charge we have, and is the road even open. That focus is what this skill adds on top of a generic "list of attractions."

When to use

Use this skill whenever the request is about driving a multi-stop trip in the US / Canada / Mexico (see read-when triggers). If the user only wants a single city guide or a flight itinerary, this is not the right skill.

Two entry modes

Detect the mode up front (see scripts/helper.py for the heuristic):

• Light mode (plan it for me): user gives a start, a rough region or destination, day count, and party/vehicle. → Run the full 7-step workflow, designing the route yourself.
• Heavy mode (verify my route): user pastes/links/screenshots an existing route. → Skip route invention. Parse their route into the schema, then verify and fill gaps: driving segmentation, overnight realism, fuel/charge coverage, reservation countdown, seasonal closures, and produce the page.

When unsure which mode, ask one short question. Otherwise infer and proceed.

The five things that make this more than a list

These are where pure-model answers fail and where this skill earns its keep:

1. Daily driving segmentation (the core). Slice the whole route into days under a sane daily drive limit, place an overnight at each segment end, and validate each day: drive ≤ limit, arrive before dark, no stop hits a closed gate, fatigue buffer. This is the road-trip equivalent of connection-checking — most AI itineraries skip it.
2. Reservation countdown. Recreation.gov campgrounds often release ~6 months out; popular timed-entry a few days out; in-park lodges up to ~13 months out. From the departure date, work backwards into a "book by" to-do list.
3. Fuel / charge planning. Gas: flag long empty stretches ("next fuel in X mi"). EV: plan a charging corridor against the vehicle's range and note whether each leg makes it, charger power, and a backup.
4. Seasonal road conditions & closures. Mountain passes that close in winter (Going-to-the-Sun, Tioga Pass, Trail Ridge Rd), wildfire/hurricane/snow season. If the travel date hits one, down-rank or reroute and say so.
5. Timezones & borders. Correct arrival times across timezone lines; for border crossings, flag documents / vehicle papers / insurance / wait times.

Workflow (7 steps)

Run scripts/helper.py "<user request>" first — it parses slots, guesses the entry mode, picks the trip region (for HTML theming), and prints what's still missing. Use its output to drive the steps below.

Step 1 — Collect requirements (slot filling)

Required: start, travel date, days, party makeup, vehicle (gas/EV/RV + range). Optional: destination/region, budget, preferences (scenic vs. fast, hike intensity, loop vs. one-way, border crossing). Only ask follow-ups for missing required slots; fill the rest with sensible defaults and proceed.

Validate place names before planning. Slot presence is not slot truth: a made-up start like "ABC" parses fine and would otherwise flow straight into a fabricated route. Run every user-supplied place — start, destination, named waypoints; in heavy mode each day's from/to towns — through python3 tools/places_client.py "<name>" and branch on its verdict: match → adopt the returned canonical name + coordinates; did-you-mean → confirm the intended place with the user (one short question, same spirit as the required-slot follow-ups); no-match → stop and ask — never plan a route around a place you could not verify; unverified (offline) → use your own judgment and ask about any name you don't recognize. A match with outsideNA: true is a real place outside US/Canada/Mexico — tell the user it's beyond this skill's coverage instead of calling it fake.

Step 2 — Route / destination planning (if not given)

Decide loop vs. one-way first (affects one-way drop fees and pacing). For region-level input ("the Southwest", "Pacific Northwest"): search candidates → seasonal & closure check → shortlist. Compute rough total miles / driving days for the shortlist and drop any "can't be driven in N days" option.

Present two candidate routes before committing (light mode only). Once the shortlist is down to viable options, draft exactly two genuinely distinct routes yourself — e.g. a faster direct corridor vs. a scenic detour, or two different geographic loops — each with a short label, a one-line summary, and rough total miles/driving days. Show both to the user and ask them to pick (or say "surprise me") before moving to Step 3. This is a single short question, same spirit as the required-slot follow-up in Step 1 — don't draft a full itinerary for either option first. If the conversation is one-shot and no reply is possible, pick the better-rated option yourself, proceed, and note the alternative you didn't take. Skip this entirely in heavy mode (the user already supplied a route) or once the user has already chosen. Carry both options into scripts/helper.compare_routes() to populate routeOptions[] (Phase-3 module below) so the rendered page shows the comparison table with the chosen route flagged.

Step 3 — Daily driving segmentation (core; see five-things #1)

1. Split by a daily drive limit (default: relaxed adults ≤ 4–5h; with kids/seniors ≤ 3–4h; user-adjustable).
2. Put an overnight at each segment end (has lodging, supplies, good for the next morning).
3. Validate: arrive before dark, no stop hits a closed gate, long legs have a fuel/charge point mid-way.
4. If infeasible: cut miles / add a night / pick a closer overnight town.
5. Surface risks explicitly in the day, e.g. "no fast charger for 180 mi on this leg — charge to full before leaving."

Rule of thumb: plan by daylight, not by odometer — a day that ends after dark fails at the trailhead, not on the map.

Step 4 — Parallel research (sub-agents)

Fan out (one concern per sub-agent, run concurrently): weather (per day), lodging/campgrounds (price + booking difficulty), fuel/charging points, attractions & tickets/permits, food, scenic byways & hikes, Reddit real-world gotchas. Delegation rule: instruct each sub-agent to hit official APIs first (NPS / NWS / Recreation.gov / Open Charge Map) and fall back to web search only on failure. See reference.md for the tool routing table and tools/.