/install face
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:
beautifiedandyoung-adultare 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 linksdata-image-idhttps://images.generated.photos/...preview URLs
Use a direct fetch first. Return 3 to 6 options max.
python3 - \x3C\x3C'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("\\u002F", "/")
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:imageortwitter: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
| Endpoint | Data Sent | Purpose |
|---|---|---|
| https://generated.photos | Filter path segments and face detail page requests | Find faces and open detail pages |
| https://images.generated.photos | Image GET requests only | Preview and transparent preview retrieval |
No other data is sent externally.
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install face - After installation, invoke the skill by name or use
/face - Provide required inputs per the skill's parameter spec and get structured output
What is Face?
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 avata... It is an AI Agent Skill for Claude Code / OpenClaw, with 302 downloads so far.
How do I install Face?
Run "/install face" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Face free?
Yes, Face is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Face support?
Face is cross-platform and runs anywhere OpenClaw / Claude Code is available (linux, darwin, win32).
Who created Face?
It is built and maintained by Iván (@ivangdavila); the current version is v1.0.0.