WayFinder Agent — AI skill for Claude Code
AI-powered microservice that turns trip filters (budget, pacing, vibe, accessibility) into a structured, real-world list of Points of Interest.
How to install WayFinder Agent
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open edvt-exe/WayFinder-Agent and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What WayFinder Agent does
AI-powered microservice that turns trip filters (budget, pacing, vibe, accessibility) into a structured, real-world list of Points of Interest. Built with FastAPI and Claude's tool-calling API — enforces strict JSON schema output, budget caps and zero hallucinated locations.
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README
WayFinder-Agent
A standalone AI microservice that turns a set of trip filters into a structured, real-world list of Points of Interest (POIs).
What it does
You send it a trip's constraints — city, number of days, transport mode, budget, pacing, interest categories, vibe, active hours per day, meals per day, and accessibility needs — and it returns a validated JSON list of real places (museums, restaurants, parks, landmarks) that match those constraints, each with coordinates, an estimated cost, and a suggested time allocation.
It's built to be plugged into a larger route-generation application as the "data retrieval" layer: it doesn't build the itinerary or the route itself, it just supplies accurate, budget-aware POI data for another system to arrange.
How it works
- FastAPI exposes a single
POST /api/v1/agent/searchendpoint that accepts the trip filters. - The filters are turned into a prompt sent to Claude (Anthropic API), guided by a system prompt that enforces real (non-hallucinated) places, realistic coordinates, category/vibe matching, and per-day meal stops.
- Claude's response is forced into a strict JSON schema via tool calling, so the output is always structured POI data — never free-form text.
- A budget-enforcement step then double-checks the total cost of all returned POIs against the trip's max budget, trimming the most expensive non-essential stops if needed, before the response is returned.
More detail on setup, configuration, and API usage will be added here as the project develops.
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