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Agent Skill · 研究检索

cosmetic-detect(化妆品检测)

cosmetic-detect 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

cosmetic-detect 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 15,644。

总安装 7,704周安装 321GitHub Stars 公开资料未说明下载 2,568核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:cosmetic-detect(化妆品检测)
来源仓库:https://github.com/deusyu/cosmetic-detect
安装命令:
openclaw skills install cosmetic-detect
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install cosmetic-detect

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

分析人脸照片以识别整容或美容手术特征。适用于医学研究、娱乐内容审核或用户画像辅助。需上传高清面部图像并明确用途声明。cosmetic-detect 属于研究检索类 Skill,可作为该场景下的辅助能力补充。结果不具备医疗诊断效力,仅作参考分析。应遵守当地隐私法规,不得滥用生物特征数据。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install cosmetic-detect;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

cosmetic-detect 怎么安装?

在终端执行 openclaw skills install cosmetic-detect。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

cosmetic-detect 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

cosmetic-detect 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

cosmetic-detect 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

cosmetic-detect 用的人多吗?

公开数据是累计安装 7,704 次,近一周安装 321 次,下载 2,568 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

cosmetic-detect 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
cosmetic-detect

化妆品检测 · 本页

7,704—只读MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
cosmetic-detect
version
1.0.0
description
Analyze facial/body photos to detect signs of cosmetic surgery or aesthetic procedures. Use when the user uploads a photo and asks to identify cosmetic work, detect plastic surgery, assess facial naturalness, check if someone has had work done, analyze before/after photos, or evaluate aesthetic procedure signs. Also trigger when users ask about specific procedures visible in photos (fillers, Botox, rhinoplasty, jaw contouring, etc.), compare photos for surgical changes, or want a "naturalness score" for a face. Works with single images, multiple comparison images, and video screenshots. 触发词:整容检测、看看有没有整、自然度评分、鉴定一下、有没有动过。

Cosmetic Surgery Detection

Core Principle

Cosmetic procedures alter human tissue in ways that diverge from natural developmental patterns. Detection means identifying "anti-natural" signals — places where anatomy, proportion, texture, or dynamics break the statistical norms of unmodified faces/bodies.

This is adversarial: the best work is designed to be undetectable. Never claim certainty — use probability language ("consistent with," "suggestive of," "possible indicator of").

Analysis Protocol

Before analysis, read references/analysis-framework.md for the detailed region-by-region indicator checklist.

Step 1: Initial Assessment

  • Image quality: Resolution, lighting, angle, makeup level. Low quality or heavy filters significantly reduce reliability — say so.
  • Apparent ethnicity/ancestry: Establishes anatomical baseline. A "high nose bridge" is normal for Europeans but statistically unusual for East Asians.
  • Apparent age: Sets expectations for skin quality, volume, aging signs.
  • Filters/editing: Check for digital manipulation (smoothing, warping, face-tuning) — flag these as NOT cosmetic surgery to avoid false positives.

Step 2: Region-by-Region Analysis

Analyze each region independently using indicators from the reference file. For each region assess:

  1. Are features within normal range for the person's apparent ethnicity and age?
  2. Are there specific indicators of surgical or non-surgical intervention?
  3. Confidence level: Low / Medium / High

Step 3: Cross-Region Coherence Check

The most powerful detection layer. Natural faces have internal consistency. Look for:

  • Ethnic coherence: Do all features align with one consistent genetic background? (e.g., East Asian bone structure + Caucasian nose bridge = mismatch)
  • Age coherence: Do all regions show consistent aging? (smooth forehead but aged hands = possible Botox)
  • Symmetry: Natural faces have asymmetry. Excessive bilateral symmetry suggests correction.
  • Proportion harmony: Do ratios between features fall within natural ranges?

Step 4: Output

## 整容检测分析 / Cosmetic Procedure Detection Analysis

### 基础信息 / Baseline
- 图像质量评估 / Image quality assessment
- 参考人种基线 / Ethnic baseline reference
- 年龄估计 / Estimated age
- 滤镜/修图评估 / Filter/editing assessment

### 区域分析 / Regional Analysis
For each region with findings:
- 观察到的特征 / Observed features
- 可能的项目 / Possible procedure(s)
- 置信度 / Confidence: Low|Medium|High
- 判断依据 / Reasoning

### 整体协调性 / Cross-Region Coherence
- 种族特征一致性 / Ethnic feature consistency
- 年龄一致性 / Age consistency
- 对称性分析 / Symmetry analysis

### 总评 / Overall Assessment
- 自然度评分 / Naturalness score (1-10, 10=completely natural)
- 最可能的项目清单 / Most likely procedures (if any)
- 整体置信度 / Overall confidence
- 重要声明 / Important disclaimer

Use the user's language. Template above is bilingual for reference.

Special Modes

Before/After Comparison

When 2+ photos of the same person at different times are provided:

  • Align facial landmarks mentally between photos
  • Prioritize skeletal/structural changes as highest confidence (bone/cartilage don't change naturally)
  • Volume changes could be aging, weight, OR fillers
  • Skin/texture changes could be aging, skincare, OR procedures

Celebrity/Public Figure

  • Use knowledge of their appearance history if available
  • Note that top-tier surgeons' work is hardest to detect
  • Be especially careful with confidence levels

Batch Analysis

When analyzing multiple people (group photo, set of photos):

  • Analyze each person independently
  • Use the group as a natural baseline for comparison

Guidelines

  • Never claim certainty. Even experienced surgeons can't always tell from photos.
  • Acknowledge limitations. Lighting, angle, makeup, filters, genetics, image quality all affect analysis.
  • Distinguish surgical vs non-surgical. Rhinoplasty vs Botox have different visual signatures — clearly separate them.
  • Stay neutral. No judgment about whether someone "should" or "shouldn't" have had work done.
  • Cultural sensitivity. Double eyelid surgery is extremely common in East Asia. Rhinoplasty is common globally. Note neutrally.

平台分布

OpenClaw

89.18%
按下载量换算2,290

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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