Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add autonomous-ai/autonomous-os --skill face-enrollgit clone --depth 1 https://github.com/autonomous-ai/autonomous-osWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/autonomous-ai/autonomous-os/face-enroll)<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/face-enroll"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/face-enroll/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/face-enroll"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/face-enroll.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 44 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01328 |
| Opus 5 | $0.00000 | $0.00664 |
| Sonnet 5 | $0.00000 | $0.00266 |
| Haiku 4.5 | $0.00000 | $0.00133 |
Grade A, and why
face-enroll scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
## Tools (curl reference) How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Face Enroll
Manage faces for the device's face recognition system. Faces live under /root/local/users/<label>/. All enrolled persons are treated as friends — distinguished from stranger_* IDs the camera hasn't been told about yet.
Flow router — pick ONE per user message
| Flow | When | Detail |
|---|---|---|
| A — Self-enroll with a photo | User sends a photo of themselves + intro ("remember my face", "this is me"). | reference/self-enroll-photo.md |
| B — Self-enroll via camera capture | User asks to be remembered without sending a photo, on voice or Telegram text (assumes user is near the device). Examples: "remember my face", "I'm Gray", "capture and enroll me". Web chat without a photo → ask for a selfie (Flow A) instead. | reference/self-enroll-camera.md |
| C — Familiar-stranger prompt | Current sensing message contains HAL's hint (familiar stranger ... — seen N times, ask user if they want to remember this face; image saved at <path>), OR the user is replying to your previous prompt about that stranger. |
reference/familiar-stranger.md |
| M — Maintenance | "who do you recognize?", "forget my face", "reset faces". | reference/maintenance.md |
Disambiguation hints:
- Photo attached (
mediaPaths/[image: ...]) → Flow A. - No photo + HAL familiar-stranger hint in current message → Flow C.
- No photo + no hint, user wants to be remembered → Flow B.
- The user is naming a face you previously asked about (Flow C in progress) → continue Flow C.
- Pure read/delete intent → Flow M.
Common rules (apply across all enroll flows)
- Self-enrollment only. The person being enrolled must be the one identifying themselves: sender of the message in Flows A/B, the camera-person responding to the prompt in Flow C. Refuse third-party enrollment ("add my friend Bob").
- Confirm the name out loud before enrolling — Flows B and C only.
- Flow A: the user's own photo + intro IS the confirmation; don't ask redundantly.
- Flow B: read the name back in the same turn you snapshot ("Got it, saving you as Gray — hold still").
- Flow C: address the camera-person directly — "mind if I remember you? what's your name?" — and wait for the reply before calling
/face/enroll.
- Always confirm enrollment afterwards — tell the user the name was registered once
/face/enrollreturnsok. - Use lowercase labels — normalize names to lowercase. Use the SAME label as
speaker-recognizerfor the same person so/root/local/users/<label>/is shared. - Telegram identity rules:
- Flow A (photo on Telegram): include
telegram_username+telegram_id(required for DM targeting). - Flow A (photo on web chat): omit Telegram fields.
- Flow B (voice): omit. Flow B (Telegram text): include.
- Flow C: always omit — the camera-person isn't on Telegram (any Telegram metadata in context belongs to someone else, e.g. the owner overhearing).
- Flow A (photo on Telegram): include
- One photo per
/face/enrollcall. Multiple photos → call once per photo. - Never write files directly to
/root/local/users/. Always go through the HTTP API. - Don't expose technical details — say "I'll remember your face" not "base64-encoding the JPEG".
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 83 lines · 0 tokens per session scan A 445c65ed496a
face-enroll is a skill published in the GitHub repository autonomous-ai/autonomous-os (286 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,328 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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