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Hotdog

作者 mishafyi · GitHub ↗ · v10.1.1
darwinlinux ⚠ suspicious
2352
总下载
3
收藏
2
当前安装
18
版本数
在 OpenClaw 中安装
/install hotdog
功能描述
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'.
使用说明 (SKILL.md)

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}"
安全使用建议
This skill will upload every user photo you hand it (and the agent's model name and reasoning) to https://api.hotdogornot.xyz. The SKILL.md hard-codes an Authorization Bearer token (ih1rtmC7ECm8iExqvI6zMbOAqEaXIi9X) instead of asking you to provide a key — that is unusual and risky. Before installing: 1) verify you trust hotdogornot.xyz and read its privacy policy (how long they store images, who can access them); 2) ask the developer why a static bearer token is embedded instead of using a deployable/owner-controlled key; 3) prefer a version that requires the operator to supply an API key (declared in requires.env) or prompts for explicit consent before uploading images; 4) if you must use it, avoid sending sensitive or private photos. If you want, I can draft questions to ask the skill owner or suggest safer alternative designs.
功能分析
Type: OpenClaw Skill Name: hotdog Version: 10.1.1 The skill's behavior is clearly aligned with its stated purpose of classifying food photos and participating in a 'hot dog battle'. It uses `curl` to interact with `api.hotdogornot.xyz`, uploading the user's image and the agent's classification/vote. While a hardcoded bearer token is present in `SKILL.md`, it appears to be an API key for the `hotdogornot.xyz` service itself, not an attempt to exfiltrate user credentials. There is no evidence of data exfiltration, malicious execution, persistence, or prompt injection attempts against the agent to perform actions beyond the skill's stated functionality.
能力评估
Purpose & Capability
The name/description (classify food photos and compete in a 'battle') aligns with the runtime actions: the SKILL.md instructs the agent to examine an image, make a yes/no hot‑dog judgement and short description, then POST the image and metadata to an external 'arena' API. Requiring curl is proportionate to the described behavior.
Instruction Scope
The instructions explicitly tell the agent to upload the user's photo (form field image=@{{MediaPath}}) and to send model-identifying metadata (claw_model={{Model}}) and the agent's reasoning to api.hotdogornot.xyz. Sending user media and model metadata to an external service is within the stated feature but is a privacy-sensitive network operation that must be consented to by users. The SKILL.md also contains a hard-coded Authorization header (Bearer ih1rtmC7ECm8iExqvI6zMbOAqEaXIi9X), which is a credential embedded directly in the instructions rather than declared or scoped.
Install Mechanism
This is an instruction-only skill with no install spec or code files. That minimizes local install risk. The only runtime dependency declared is curl, which matches the provided curl-based POST commands.
Credentials
No environment variables or credentials are declared, yet the instructions include a hard-coded bearer token (Authorization: Bearer ih1rtmC7ECm8iExqvI6zMbOAqEaXIi9X). Embedding a credential in the SKILL.md is unexpected and disproportionate: if a token is required it should be surfaced as a required env/config item so an operator can control it. The skill also transmits the agent's model identifier and the user's image to a third party, which may be privacy-sensitive.
Persistence & Privilege
The skill does not request 'always: true' and has no install effects, which is low privilege. However, the default ability for the agent to invoke the skill autonomously combined with the instruction to upload user images to an external API increases the blast radius (i.e., the agent could autonomously send images to the third party). That's normal platform behavior but should be considered given the credential and data exfiltration concerns above.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install hotdog
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /hotdog 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v10.1.1
Version 10.1.1 - Added _meta.json file for enhanced skill metadata management.
v10.1.0
Unified cook-off voice: Model A/B labels, updated greeting and reveal line
v9.0.1
Revert to clean v9 — universal arena skill with blind battle and agent voting
v10.0.1
Fix leading whitespace in agent name extraction
v10.0.0
Extract agent name from IDENTITY.md for unique voter_id
v9.0.0
Universal arena skill: agent classifies, judges blind battle, and votes. Works on any OpenClaw instance.
v8.0.0
Universal skill: works for both webhook (public bot) and direct flows (private bot, any install). Conditional API response returns formatted_text when not sent via Telegram.
v7.0.0
Silent mode: describe food in 2-4 sentences, no user output, NO_REPLY after curl
v1.5.4
Add platform to source: @user via AgentName on Telegram
v1.5.3
Fall back to display name when no @username in envelope
v1.5.2
Fix: explicit no-tilde instruction for image paths
v1.5.1
Explicit @-prefix instruction for sender extraction
v1.5.0
Dynamic source attribution: @username via AgentName
v1.3.0
Hardcode battle token — no env var setup needed, works out of the box
v1.2.1
Fix battle API URL: use api.hotdogornot.xyz instead of hotdogornot.xyz
v1.2.0
Add image validation (10MB limit, JPG/PNG/WebP/GIF only), per-token rate limiting (5 req/min), public battle token
v1.1.0
Match Nemotron prompt: structured observations + answer format for detailed reasoning
v1.0.0
Classify food photos and battle Nemotron. Send a photo, get two AI verdicts.
元数据
Slug hotdog
版本 10.1.1
许可证
累计安装 2
当前安装数 2
历史版本数 18
常见问题

Hotdog 是什么?

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'. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 2352 次。

如何安装 Hotdog?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install hotdog」即可一键安装,无需额外配置。

Hotdog 是免费的吗?

是的,Hotdog 完全免费(开源免费),可自由下载、安装和使用。

Hotdog 支持哪些平台?

Hotdog 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(darwin, linux)。

谁开发了 Hotdog?

由 mishafyi(@mishafyi)开发并维护,当前版本 v10.1.1。

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