elsewhere-companion

A cross-space digital travel companion. Creates a virtual character (旅伴) who travels to real destinations and sends postcard-like updates with AI-generated images aligned to real-world time, weather, and geography. Use when: user wants to create a travel companion, plan a companion trip, check on their companion's journey, or says words like "elsewhere", "旅伴", "travel companion", "明信片", "出去走走".

A digital travel companion who journeys to real places and sends you postcard-like updates.

Prerequisites

1. Python 3 must be installed
2. GEMINI_API_KEY environment variable must be set (create data/.env with GEMINI_API_KEY=...)
3. Python packages: google-genai, jinja2, Pillow, python-dotenv (install via pip install -r requirements.txt)

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Global Constraints

• Language: Always communicate with the user in their language (the language they are using in the current conversation). Do not switch to other languages unless explicitly requested.

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Workflow Overview

There are three phases: Onboarding → Trip Planning → Traveling (automated).

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Phase 1: Onboarding (First-time setup)

If data/persona.json does not exist or has an empty basic_info.name, the companion hasn't been created yet. Collect the following information from the user:

1. name - the companion's name
2. relation - relationship (e.g., childhood friend, penpal, imaginary sibling)
3. personality - a few words (e.g., curious, poetic, a little clumsy)
4. toneOfVoice - e.g., casual and warm, literary, playful
5. appearance - hair, clothing style, vibe description

After collecting all information, create the persona file:

bash

python -c "
import json, os
os.makedirs('data', exist_ok=True)
persona = {
    'basic_info': {
        'name': '<name>',
        'relation': '<relation>',
        'personality': '<personality>',
        'tone_of_voice': '<toneOfVoice>',
    },
    'appearance': {
        'description': '<appearance>',
        'reference_image_path': './assets/personas/persona_ref.png',
    },
}
with open('data/persona.json', 'w', encoding='utf-8') as f:
    json.dump(persona, f, ensure_ascii=False, indent=2)
print('Persona saved to data/persona.json')
"

Then ask the user to upload a reference photo and save it to assets/personas/persona_ref.png.

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Phase 2: Trip Planning

Ask the user: "Where should {name} go next?"

Accept a destination suggestion, then generate the itinerary:

bash

python $CLAUDE_SKILL_DIR/scripts/generate_itinerary.py <destination> [--origin <city>] [--days <num>]

Show the generated itinerary to the user and ask for confirmation. Once confirmed, proceed to Phase 3.

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Phase 3: Traveling (Automated)

Starting the journey

Start the heartbeat loop:

text

/loop 15m !`python $CLAUDE_SKILL_DIR/scripts/run_cron.py`

The loop runs run_cron.py every 15 minutes. It automatically:

1. Checks the current time against the itinerary timeline
2. Updates node statuses (PENDING → ACTIVE → COMPLETED)
3. Generates text + image content via Gemini (when triggered by the state machine)
4. Renders the appropriate Markdown template
5. Prints the result for delivery

The state machine rules (from references/state_machine.md):

• State transitions (PENDING→ACTIVE): always triggers a message
• 45-minute interval: messages are separated by at least 45 minutes
• Attraction first visit: always triggers
• Attraction subsequent visits: 40% probability for 2nd, 10% for 3rd
• Max 1 message per cron tick

Checking status

bash

python $CLAUDE_SKILL_DIR/scripts/run_cron.py --check-only

Ending the journey

When all nodes are COMPLETED, stop the loop:

text

/loop stop

Tell the user the trip is over and ask if they'd like to plan a new one.

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Manual postcard generation

If you need to generate a postcard for a specific node:

bash

python $CLAUDE_SKILL_DIR/scripts/generate_post.py <node_id>

Then render it with the template:

bash

python $CLAUDE_SKILL_DIR/scripts/render_output.py --context '<json_context>'

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File reference

• Scripts: $CLAUDE_SKILL_DIR/scripts/
• Templates: $CLAUDE_SKILL_DIR/templates/
• Runtime data: data/ (itinerary.json, persona.json)
• Generated images: assets/generated/