🧪 Skills

Hotdog

Hot dog or not? Classify food photos and battle Nemotron. Use when a user sends a food photo, asks if something is a hot dog, or says 'hotdog', '/hotdog', or 'hot dog battle'.

v10.1.1
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Description


name: hotdog version: 10.0.0 description: "Hot dog or not? Classify food photos and battle Nemotron. Use when a user sends a food photo, asks if something is a hot dog, or says 'hotdog', '/hotdog', or 'hot dog battle'." homepage: https://hotdogornot.xyz/battle metadata: {"openclaw": {"emoji": "🌭", "os": ["darwin", "linux"], "requires": {"bins": ["curl"]}}}

Hot Dog or Not — Battle Skill

No photo

If triggered without a photo, reply EXACTLY (nothing more):

🌭 Hot Dog or Not — AI Cook-Off

Send me a food photo and I'll classify it head-to-head with Nemotron.
I'll judge whose description was better — blind.

📸 Send a photo to start
🏆 Scoreboard: https://hotdogornot.xyz/battle

With a photo

  1. Look at the image. Describe the food in 2-3 sentences. Decide: is it a hot dog (sausage in a bun)? Your ANSWER is "yes" or "no". Your DESCRIPTION is your sentences. Do NOT output anything yet.

  2. Send your classification to the battle API. Replace ANSWER and DESCRIPTION:

exec: curl -s -X POST "https://api.hotdogornot.xyz/api/arena/round" -H "Authorization: Bearer ih1rtmC7ECm8iExqvI6zMbOAqEaXIi9X" -F "image=@{{MediaPath}}" -F "claw_model={{Model}}" -F "claw_answer=ANSWER" -F "claw_reasoning=DESCRIPTION"
  1. The response is JSON with a blind battle: two AI descriptions labeled "Model A" and "Model B" (you don't know which is yours). Read formatted_text, round_id, and first_side from the JSON.

  2. Judge: which response describes the image more accurately? Pick "first", "second", or "tie". Then submit your vote — replace ROUND_ID, FIRST_SIDE, and PICK:

exec: curl -s -X POST "https://api.hotdogornot.xyz/api/arena/vote/submit" -H "Content-Type: application/json" -d '{"round_id":"ROUND_ID","voter_id":"agent","voted_for":"PICK","first_side":"FIRST_SIDE"}'
  1. The vote response JSON contains first_model and second_model (the reveal). Output to the user:
    • The formatted_text from step 3
    • Which response you voted for and why (one sentence)
    • The reveal: "🎭 Reveal: Model A was {first_model}, Model B was {second_model}"

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