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evo-travel-planning

Build multi-day travel itineraries from structured databases (cities, accommodations, restaurants, attractions, driving distances) with robust constraint validation, budget tracking, and pet-friendly filtering.

tasks-evolved/travel-planning/environment/skills/evo-travel-planning/SKILL.md

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Sep 10, 2026
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# evo-travel-planning

## Purpose
Build multi-day travel itineraries from structured CSV/text databases covering cities, accommodations, restaurants, attractions, and driving distances. Handles complex constraints including pet-friendly accommodations, cuisine preferences, budget limits, multi-city routing, and transportation restrictions.

## Key Rules
1. All data must come from database files in `/app/data/` — never use LLM memory for POIs.
2. **Pet-friendly accommodations**: `house_rules` column must NOT contain "No pets" (use `na=False` to handle NaN safely per Pandas 2.0.3 best practices).
3. Output accommodation field MUST contain "Pet-friendly" prefix when pet-friendly is required.
4. Cuisine coverage verified from restaurant `Cuisines` field, not restaurant names.
5. All 5 tool names must appear in `tool_called`: `search_cities`, `search_accommodations`, `search_restaurants`, `search_attractions`, `search_driving_distance`.
6. Attractions separated by semicolons with trailing semicolon (e.g., `"Attraction A;Attraction B;"`).
7. Transportation format: `"Self-driving: from A to B"` or `"-"` for same-city days.
8. `current_city`: city name for same-city days, or `"from A to B"` for transit days.