Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Content Creation
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'.
skill openclawclawhub Free
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'.
โฌ 0 downloads โ
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, _meta.json
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 10.1.1
Provenance
- Publisher
- mishafyi
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
No photo
If triggered without a photo, reply EXACTLY (nothing more): ๐ญ Hot Dog or Not โ 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 โ blind. ๐ธ Send a photo to start ๐ Scoreboard: https://hotdogornot.xyz/battle
With a photo
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. 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" 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. Judge: which response describes the image more accurately? Pick "first", "second", or "tie". Then submit your vote โ 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"}' 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: "๐ญ Reveal: Model A was {first_model}, Model B was {second_model}"
Category context
Writing, remixing, publishing, visual generation, and marketing content production.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Config
- SKILL.md
- _meta.json