Fal Vision
nexu-io/open-design
Analyze images — segment objects, detect, run OCR, describe, and answer visual questions via fal.ai vision models.
Use ONLY to follow/track/watch a movable physical OBJECT vision can recognize (cup, bottle, phone, hand, person, pen, book, remote, toy, keys, pet, a specific face).
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill servo-tracking -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System servo-tracking --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/servo-tracking .claude/skills/servo-tracking && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "servo-tracking" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/servo-tracking into .claude/skills/servo-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "servo-tracking", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/servo-trackingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill servo-tracking -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System servo-tracking --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/servo-tracking .agents/skills/servo-tracking && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "servo-tracking" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/servo-tracking into .agents/skills/servo-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "servo-tracking", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill servo-tracking -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System servo-tracking --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/servo-tracking .cursor/skills/servo-tracking && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "servo-tracking" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/servo-tracking into .cursor/skills/servo-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "servo-tracking", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/autonomous-ai/Physical-AI-Operating-System.git --path skills/servo-tracking--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill servo-tracking -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System servo-tracking --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/servo-tracking .gemini/skills/servo-tracking && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "servo-tracking" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/servo-tracking into .gemini/skills/servo-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "servo-tracking", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install autonomous-ai/Physical-AI-Operating-System servo-trackingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill servo-tracking -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/servo-tracking .github/skills/servo-tracking && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "servo-tracking" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/servo-tracking into .github/skills/servo-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "servo-tracking", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill servo-tracking -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System servo-tracking --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/servo-tracking .opencode/skills/servo-tracking && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "servo-tracking" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/servo-tracking into .opencode/skills/servo-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "servo-tracking", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
servo-trackingUse ONLY to follow/track/watch a movable physical OBJECT vision can recognize (cup, bottle, phone, hand, person, pen, book, remote, toy, keys, pet, a specific face).
Servo Tracking is an agent skill from autonomous-ai/Physical-AI-Operating-System. Use ONLY to follow/track/watch a movable physical OBJECT vision can recognize (cup, bottle, phone, hand, person, pen, book, remote, toy, keys, pet, a specific face). NEVER use for furniture or fixed locations (desk, table, wall, floor, ceiling, door, window, workspace, room) — those are directions; use servo-control /servo/aim. NEVER use for direction words (left, right, up, down, center). If the user combines a direction AND an object ("look at the desk and follow the cup", "point at the table and track the…
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill.json`).
The repository describes itself as: The open-source operating system for physical AI. The licence is Apache-2.0.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit f1b9ebe. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Servo Tracking loads about 1.3k tokens when it runs. Until then it costs about 182 tokens; SKILL.md has 580 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from autonomous-ai/Physical-AI-Operating-System at commit f1b9ebe, republished under its Apache-2.0 licence (© autonomous-ai). 580 words, ~1,310 tokens.
.claude/skills/servo-tracking/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Tracks and follows any object by name. YOLOWorld detects the object in the camera frame, TrackerVit follows it in real-time with servo movement.
/servo/aim FIRST so the camera is pointing at the right region before YOLO detection runs. Then fire /servo/track. The aim should complete in ~2s before the track call takes over.[HW:/servo/track:{"target":["<label1>","<label2>"]}] — the device detects and follows.target accepts a list of candidate labels. Pass 2-4 synonyms/variants to maximise the chance YOLOWorld finds the object on the first try.{"target":"cup"}) for backward compatibility, but the list form is preferred when the object could reasonably have multiple names.[HW:/servo/track/stop:{}].Input: "Look at the desk and follow the cup"
Output: [HW:/servo/aim:{"direction":"desk"}][HW:/servo/track:{"target":["cup","mug","coffee cup"]}] Looking at the desk and locking onto the cup.
Input: "Point at the table and track my phone"
Output: [HW:/servo/aim:{"direction":"desk"}][HW:/servo/track:{"target":["phone","smartphone","mobile phone"]}] Aimed at the table, tracking your phone.
Input: "Follow the cup"
Output: [HW:/servo/track:{"target":["cup","mug","coffee cup"]}] OK, following the cup!
Input: "Look at the bottle"
Output: [HW:/servo/track:{"target":["bottle","water bottle","plastic bottle"]}] Watching the bottle.
Input: "Track that person"
Output: [HW:/servo/track:{"target":["person","man","woman"]}] Following them now.
Input: "Watch my phone"
Output: [HW:/servo/track:{"target":["phone","smartphone","mobile phone"]}] Got it, tracking your phone.
Input: "Follow the teddy bear"
Output: [HW:/servo/track:{"target":["teddy bear","stuffed animal","plush toy"]}] Tracking the teddy bear!
Input: "Stop following" / "Stop tracking"
Output: [HW:/servo/track/stop:{}] Stopped tracking.
Input: "What can you track?" Output: I can track most common objects — cups, bottles, phones, laptops, books, people, bags, and more. Just tell me what to follow!
No exec/curl needed. Inline markers at start of reply:
[HW:/servo/track:{"target":["cup","mug","coffee cup"]}] Following the cup.
[HW:/servo/track:{"target":["person"]}] Tracking you now.
[HW:/servo/track/stop:{}] Stopped tracking.Prefer a list of 2-4 candidate labels in English. YOLOWorld evaluates all candidates and picks the highest-confidence detection across the set — synonyms increase the chance of a successful first-try detection when the user's wording doesn't exactly match COCO/training vocabulary.
Common objects: person, cup, bottle, glass, phone, laptop, keyboard, mouse, book, pen, notebook, bag, chair, monitor, remote control, plate, bowl, plant, vase, clock, lamp, speaker, headphones, watch, glasses, hat, shoe, toy, ball, teddy bear.
Any label works (open-vocabulary detection). Don't include too many unrelated items in the list — that risks matching a nearby but wrong object.
target as a list of 2-4 English synonyms for better first-try detection. Avoid packing unrelated labels into the list.© autonomous-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/servo-tracking of autonomous-ai/Physical-AI-Operating-System.
Open the folder on GitHubat commit f1b9ebe
Servo Tracking next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Servo Tracking this skillautonomous-ai/Physical-AI-Operating-System | 381 | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Fal Visionnexu-io/open-design | 100k | — | ~295 | Automated safety check: Pass | Apache-2.0 | |
| Senior Computer Visiondavila7/claude-code-templates | 32k | 3 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Horizon Trackruvnet/ruflo | 74k | — | ~744 | Automated safety check: Notes | MIT | |
| Senior Computer Visionalirezarezvani/claude-skills | 28k | 2 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Vision Sftwshobson/agents | 40k | — | ~2k | Automated safety check: Pass | MIT |
nexu-io/open-design
Analyze images — segment objects, detect, run OCR, describe, and answer visual questions via fal.ai vision models.
davila7/claude-code-templates
World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems.
ruvnet/ruflo
Track long-horizon objectives across multiple sessions with milestone checkpoints, progress persistence, and drift detection
alirezarezvani/claude-skills
Computer vision engineering skill for object detection, image segmentation, and visual AI systems.
wshobson/agents
Fine-tune vision-language models (VLMs) with supervised learning on image+text data.
gridaco/grida
Query images with a local Ollama vision model without loading the image into the main agent context.
autonomous-ai/Physical-AI-Operating-System
Legacy Autonomous Buddy control for explicitly requested Buddy coding sessions.
autonomous-ai/Physical-AI-Operating-System
Push Claude Code activity to the user's device (e.g. An agent skill from autonomous-ai/Physical-AI-Operating-System.
autonomous-ai/Physical-AI-Operating-System
Operate apps/websites on the paired Mac via Buddy: Calendar, Notes, forms, screenshots, files.
autonomous-ai/Physical-AI-Operating-System
Discover and use linked third-party services (Gmail, Google Calendar, Google Drive, Notion, Figma, Asana, Linear, GitHub, Ahrefs, Facebook Fan Page and others).
autonomous-ai/Physical-AI-Operating-System
Delegate digital work to agents on the computer paired through Harness; discover Store packages and prepare an agent when needed.
autonomous-ai/Physical-AI-Operating-System
Low-level speaker and microphone hardware control — adjust volume, play test tones, record raw audio.
Use ONLY to follow/track/watch a movable physical OBJECT vision can recognize (cup, bottle, phone, hand, person, pen, book, remote, toy, keys, pet, a specific face). Servo Tracking is an agent skill from autonomous-ai/Physical-AI-Operating-System. Use ONLY to follow/track/watch a movable physical OBJECT vision can recognize (cup, bottle, phone, hand, person, pen, book, remote, toy, keys, pet, a specific face).
Servo Tracking fits situations like: fixed locations (desk; room) — those are directions; use servo-control /servo/aim; direction words (left.
Run `npx skills add autonomous-ai/Physical-AI-Operating-System --skill servo-tracking -a claude-code`. Or copy the skill folder (skills/servo-tracking in autonomous-ai/Physical-AI-Operating-System) into .claude/skills/servo-tracking in your project. Claude Code loads it when a task matches its description.
Run `npx skills add autonomous-ai/Physical-AI-Operating-System --skill servo-tracking -a codex`. Or copy the skill folder (skills/servo-tracking in autonomous-ai/Physical-AI-Operating-System) into .agents/skills/servo-tracking in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add autonomous-ai/Physical-AI-Operating-System --skill servo-tracking -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/servo-tracking, .gemini/skills/servo-tracking, .github/skills/servo-tracking and .opencode/skills/servo-tracking in your project.
SKILL.md names no scripts, command-line tools or credentials: Servo Tracking is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Servo Tracking is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Servo Tracking: Fal Vision (nexu-io/open-design, 100k stars), Senior Computer Vision (davila7/claude-code-templates, 32k stars), Horizon Track (ruvnet/ruflo, 74k stars) and Senior Computer Vision (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
autonomous-ai (a GitHub organization) maintains it in autonomous-ai/Physical-AI-Operating-System, which has 381 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on October 8, 2026.
Source: autonomous-ai/Physical-AI-Operating-System on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.