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faceface 控制

Agent Skill

face 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。

总安装

8,914

周安装

379

GitHub Stars

公开资料未说明

下载量

3,123
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:face(face 控制)
来源仓库:https://github.com/ivangdavila/face
安装命令:
openclaw skills install face
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 face

简介

用于为代理提供人性化头像选择。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

  • 支持性别控制和透明背景选项。face 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 生成可重复使用的个人资料链接。
  • 使用时需确认头像用途是否符合内容政策。
  • 安装前建议检查维护状态和是否会触发外部图片服务调用。

SKILL.md

name
Face
slug
face
version
1.0.0
homepage
https://clawic.com/skills/face
description
Put a human face on your agent with fast avatar shortlists, gender control, transparent options, and reusable profile links. Use when the user wants an avatar, profile face, or group image.
changelog
Refines the positioning around putting a human face on the agent with faster avatar selection.
metadata
{"clawdbot":{"emoji":"👤","requires":{"bins":["curl","python3"]},"os":["linux","darwin","win32"]}}

Put a Face on Your Agent

Use this skill to give an agent, persona, group, or Telegram surface a real human-looking face fast.

The job is simple:

  • open a stable face listing URL
  • extract a small shortlist of faces
  • send the options to the user to choose
  • if one is approved, reuse that link as the avatar or suggest saving it in identity

Core Workflow

1. Start from the stable URL

Default to:

https://generated.photos/faces/beautified/{gender}/young-adult

Notes:

  • beautified and young-adult are the best default for this use case
  • gender is the main parameter that usually matters
  • the site may also accept .../young-adult/{gender}, but the canonical form resolves to .../{gender}/young-adult

2. Only trust filters the site already exposes

From the page HTML, the route families that were verified as stable are:

  • head pose: front-facing, left-facing, right-facing
  • race: asian-race, black-race, latino-race, white-race
  • eye color: brown-eyes, grey-eyes, blue-eyes, green-eyes
  • hair color: brown-hair, black-hair, blond-hair
  • hair length: short, medium, long
  • emotion: joy, neutral

Do not invent deeper URL combinations from memory. If the user wants narrower filtering, open the base page and follow the exact links that page emits.

3. Extract faces from HTML before using a browser

The page already contains:

  • /face/... detail links
  • data-image-id
  • https://images.generated.photos/... preview URLs

Use a direct fetch first. Return 3 to 6 options max.

python3 - <<'PY'
import json
import re
from urllib.request import Request, urlopen

url = "https://generated.photos/faces/beautified/female/young-adult"
raw = urlopen(Request(url, headers={"User-Agent": "Mozilla/5.0"})).read().decode()

cards = re.findall(
    r'href="(/face/[^"]+)".*?data-image-id="([^"]+)".*?src="(https://images.generated.photos[^"]+)"',
    raw,
    re.S,
)
transparent = {
    image_id: thumb.replace("\\/", "/")
    for image_id, thumb in re.findall(
        r'id:"([^"]+)".*?transparent:\{thumb_url:"([^"]+)"',
        raw,
    )
}

for n, (detail, image_id, thumb) in enumerate(cards[:6], 1):
    print(json.dumps({
        "n": n,
        "detail": "https://generated.photos" + detail,
        "thumb": thumb,
        "transparent": transparent.get(image_id),
    }))
PY

4. Treat background as extraction, not routing

Do not model background as a clean route parameter.

What was verified:

  • the page UI shows a background area
  • the route itself does not expose a simple stable public background parameter
  • transparent versions appear in embedded data as transparent.thumb_url

Rule:

  • if the user wants a transparent avatar, prefer transparent.thumb_url
  • if the user wants a bigger preview, open the chosen detail page and use the 512px og:image or twitter:image

5. Always keep the user in the loop

Default output should be:

  • 3 to 6 numbered options
  • one normal preview per option
  • transparent preview too when available
  • the detail page link

Do not auto-pick unless the user asks.

6. Reuse the chosen face properly

Once the user chooses one:

  • propose using it as the avatar for the agent, group, Telegram profile, or similar
  • if it is their long-term face, suggest storing the chosen link in identity
  • keep the detail page link, not just the image preview URL

Recommended Response Shape

When you answer, keep it compact:

I found 4 options for your agent face.

1. Option A
   Detail: ...
   Preview: ...
   Transparent: ...

2. Option B
   Detail: ...
   Preview: ...
   Transparent: ...

Tell me which one you want and I’ll prepare it as the avatar.

Common Mistakes

  • guessing URL variants instead of following the page's real filters
  • trying to control background through the route
  • showing too many faces at once
  • saving only the preview URL instead of the detail link
  • changing an avatar without explicit approval

External Endpoints

EndpointData SentPurpose
https://generated.photosFilter path segments and face detail page requestsFind faces and open detail pages
https://images.generated.photosImage GET requests onlyPreview and transparent preview retrieval

No other data is sent externally.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

83.49%
按下载量换算2,607

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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