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 agentmods add skills/gaelic-ghost/socket/arkit-face-body-tracking-workflownpx skills add gaelic-ghost/socket --skill arkit-face-body-tracking-workflowgit clone --depth 1 https://github.com/gaelic-ghost/socketWrote 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/gaelic-ghost/socket/arkit-face-body-tracking-workflow)<a href="https://agentmods.dev/skills/gaelic-ghost/socket/arkit-face-body-tracking-workflow"><img src="https://agentmods.dev/badge/skills/gaelic-ghost/socket/arkit-face-body-tracking-workflow.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00082 | $0.01211 |
| Opus 5 | $0.00041 | $0.00606 |
| Sonnet 5 | $0.00016 | $0.00242 |
| Haiku 4.5 | $0.00008 | $0.00121 |
Grade A, and why
arkit-face-body-tracking-workflow scanned grade A with 0 findings 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 4d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ARKit Face and Body Tracking Workflow
Purpose
Guide ARKit face and body tracking while keeping TrueDepth geometry, body skeletons, Vision image analysis, Local Authentication, camera capture, rendering, and sensitive-data handling explicitly separate.
When To Use
- Use for
ARFaceTrackingConfiguration,ARFaceAnchor, face geometry, blend shapes, eye transforms,ARBodyTrackingConfiguration,ARBodyAnchor,ARSkeleton3D, joint transforms, and scale estimation. - Recommend Local Authentication for Face ID or Touch ID authentication; ARKit never exposes enrolled biometric templates.
- Recommend Vision for face rectangles/landmarks or 2D body/hand/animal pose analysis in ordinary images and video frames.
Single-Path Workflow
- Classify the request:
- face position/orientation or topology
- blend shapes or face-driven animation
- eye transforms or gaze-adjacent effects
- world-plus-face tracking
- body anchor, skeleton, joint pose, or scale
- rendering, privacy, performance, or correctness repair
- Apply the Apple docs gate:
- read current ARKit face/body and Local Authentication documentation
- state the documented behavior relied on
- apply
../../shared/references/apple-spatial-data-privacy-contract.md - check configuration support, supported video formats, maximum tracked faces, world-tracking support, automatic scale support, and physical device capability
- Choose one tracking configuration:
- use
ARFaceTrackingConfigurationfor supported TrueDepth face tracking and optional documented world tracking - use
ARBodyTrackingConfigurationfor supported 3D body tracking - do not imply simultaneous configurations or combine them through a generic tracking manager
- use
- Preserve typed tracking data:
- keep anchor identifier, transform, geometry/topology, blend-shape coefficients, eye transforms, skeleton definition, joint names/transforms, estimated scale, timestamps, and tracking state inspectable
- attach results to the correct frame/session generation
- Define the consumer boundary:
- hand rendering and animation to RealityKit, SceneKit, Metal, SwiftUI, or AppKit/UIKit as the actual UI requires
- hand 2D image analysis to Vision and authentication to Local Authentication
- Return documented behavior, capability evidence, configuration, coordinate/skeleton contract, privacy and retention policy, diagnostics, physical-device validation, and handoffs.
What ships with it
4 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.
- 4d ago First seen · 86 lines · 82 tokens per session scan A 240135c4e3ab
arkit-face-body-tracking-workflow is a skill published in the GitHub repository gaelic-ghost/socket (7 stars, last pushed 9d ago), licensed Apache-2.0. It adds 82 tokens to every session and 1,211 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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