Agent skill

Tracking And Solutions

by VectorSpaceLab in VectorSpaceLab/AREX-Skill

A skill your agent uses for Ultralytics track mode, tracker YAML selection, persistent object IDs, and YOLO Solutions such as counting, heatmaps, speed, queue, region, similarity search, and…

AGPL-3.0Auto-check passedAI & LLM Engineering

Install Tracking And Solutions

skills CLI
$ npx skills add VectorSpaceLab/AREX-Skill --skill tracking-and-solutions -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install VectorSpaceLab/AREX-Skill tracking-and-solutions --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/repositories/repo-skills/ultralytics/sub-skills/tracking-and-solutions .claude/skills/tracking-and-solutions && rm -rf skills-src

Use ~/.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/

Facts

Skill name
tracking-and-solutions
GitHub stars
330
Token cost
~871 tokens
SKILL.md length
254 words
Files
5 (incl. scripts, references)
Skills in repo
159
Repo updated
First seen
Licence
AGPL-3.0

At a glance

A skill your agent uses for Ultralytics track mode, tracker YAML selection, persistent object IDs, and YOLO Solutions such as counting, heatmaps, speed, queue, region, similarity search, and…

  • Works in 6 steps: Confirm the model, task, and source are… → For direct tracking, use… → For CLI tracking, use the Ultralytics… → …
  • Ultralytics track mode
  • SKILL.md covers Route Elsewhere, Fast Path, Safe Examples and References
  • Runs Python scripts from its folder; calls python

What it does

Tracking And Solutions is an agent skill from VectorSpaceLab/AREX-Skill. Use for Ultralytics track mode, tracker YAML selection, persistent object IDs, and YOLO Solutions such as counting, heatmaps, speed, queue, region, similarity search, and Streamlit inference.

Its SKILL.md is about 870 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/api-reference.md`, `references/troubleshooting.md` and `references/workflows.md`).

It sits in AI & LLM Engineering, covering Computer vision and Vector databases. It works with Streamlit. The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is AGPL-3.0.

When your agent uses it

  • Ultralytics track mode
  • Tracker YAML selection
  • Persistent object IDs
  • YOLO Solutions such as counting

Example prompts

  • “/tracking-and-solutions”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Confirm the model, task, and source are tracking-compatible; classification does not support mode=track.
  2. For direct tracking, use YOLO(...).track(source=..., tracker="botsort.yaml", stream=True, show=False) for full videos, or persist=True…
  3. For CLI tracking, use the Ultralytics arg=value form: yolo track model=yolo26n.pt source=video.mp4 tracker=bytetrack.yaml conf=0.25.
  4. Pick a tracker using scripts/choose_tracker.py and then tune only copied YAML values; keep tracker_type unchanged in custom tracker YAMLs.
  5. For counting, heatmap, speed, queue, region, trackzone, similarity search, or Streamlit inference, use references/workflows.md and pass…
  6. Check references/troubleshooting.md before advising installs, downloads, GUI display, webcam/network streams, GPU/FP16, or optional…

What it can do on your machine

Read from SKILL.md and the folder at commit ac3fe1a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tracking And Solutions loads about 871 tokens when it runs, and up to ~5.5k if it reads all its reference files. Until then it costs about 54 tokens; SKILL.md has 254 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~871
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.5k

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.

Safety

Auto-check passed

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); the scripts in this folder are not scanned.

SKILL.md

The full file from VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its AGPL-3.0 licence (© VectorSpaceLab). 254 words, ~871 tokens.

Download SKILL.mdSave it as .claude/skills/tracking-and-solutions/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
tracking-and-solutions
description
Use for Ultralytics track mode, tracker YAML selection, persistent object IDs, and YOLO Solutions such as counting, heatmaps, speed, queue, region, similarity search, and Streamlit inference.
disable-model-invocation
true
metadata.disco-role
operating
license
AGPL 3.0

Tracking and Solutions

Use this sub-skill when the user asks for model.track(...), yolo track, tracker configuration, object IDs across video frames, or Ultralytics Solutions workflows such as object counting, heatmaps, speed estimation, queue management, region counting, similarity search, and Streamlit live inference.

Route Elsewhere

  • Generic predict/result parsing without persistent IDs: ../inference-and-results/SKILL.md
  • Dataset YAMLs, config files, class names, and path validation: ../data-and-configuration/SKILL.md
  • Train/val runs, metrics, and dataset evaluation: ../training-and-validation/SKILL.md
  • Export formats, deployment runtimes, benchmarks, and engine-specific failures: ../export-and-deployment/SKILL.md
  • Model family/task selection before choosing weights: ../model-families-and-tasks/SKILL.md
  • Repository maintenance, tests, and development workflows: ../repo-development/SKILL.md

Fast Path

  1. Confirm the model, task, and source are tracking-compatible; classification does not support mode=track.
  2. For direct tracking, use YOLO(...).track(source=..., tracker="botsort.yaml", stream=True, show=False) for full videos, or persist=True when feeding frames manually.
  3. For CLI tracking, use the Ultralytics arg=value form: yolo track model=yolo26n.pt source=video.mp4 tracker=bytetrack.yaml conf=0.25.
  4. Pick a tracker using scripts/choose_tracker.py and then tune only copied YAML values; keep tracker_type unchanged in custom tracker YAMLs.
  5. For counting, heatmap, speed, queue, region, trackzone, similarity search, or Streamlit inference, use references/workflows.md and pass source, model, region, classes, tracker, device, conf, and iou explicitly.
  6. Check references/troubleshooting.md before advising installs, downloads, GUI display, webcam/network streams, GPU/FP16, or optional ReID/search/Streamlit dependencies.

Safe Examples

Direct tracking API:

python
from ultralytics import YOLO

model = YOLO("yolo26n.pt")
for result in model.track(source="video.mp4", stream=True, tracker="bytetrack.yaml", conf=0.25, show=False):
    boxes = result.obb if result.obb is not None else result.boxes
    if boxes is not None and boxes.is_track:
        print(boxes.id.cpu().tolist())

Manual frame loop with persistent IDs:

python
results = model.track(frame, persist=True, tracker="botsort.yaml", verbose=False)

Solutions CLI with a polygon region:

bash
yolo solutions region source="video.mp4" model=yolo26n.pt tracker=botsort.yaml region="[(20,400),(1080,400),(1080,360),(20,360)]" show=False

Tracker recommendation helper:

bash
python sub-skills/tracking-and-solutions/scripts/choose_tracker.py --goal reid --moving-camera --prefer-stable-ids

References

  • Tracking APIs, CLI commands, tracker YAMLs, and customization: references/api-reference.md
  • Solutions workflows, class/CLI mapping, regions, outputs, and optional apps: references/workflows.md
  • Workflow-specific failure diagnosis and recovery: references/troubleshooting.md
  • Safe tracker recommendation helper: scripts/choose_tracker.py

© VectorSpaceLab, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in skills/repositories/repo-skills/ultralytics/sub-skills/tracking-and-solutions of VectorSpaceLab/AREX-Skill.

  • SKILL.md
  • references/api-reference.md
  • references/troubleshooting.md
  • references/workflows.md
  • scripts/choose_tracker.py

Open the folder on GitHubat commit ac3fe1a

Compare with similar skills

Tracking And Solutions 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.

Tracking And Solutions compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tracking And Solutions this skillVectorSpaceLab/AREX-Skill330—~871Automated safety check: PassAGPL-3.0
Cookbook Aimldatabricks-solutions/databricks-apps-cookbook183—~1.7kAutomated safety check: PassCustom licence
Chroma Vector DatabaseOrchestra-Research/AI-Research-SKILLs13k7 repos~2.3kAutomated safety check: PassMIT
Codebase Managementgiancarloerra/SocratiCode3.3k1 repos~1.8kAutomated safety check: PassAGPL-3.0
Hermes Memory Providersmnemosyne-oss/mnemosyne3.4k—~1.8kAutomated safety check: PassMIT
Flowflow Spacesmirkobozzetto/flowflow171—~1kAutomated safety check: PassEUPL-1.2

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Works with

Questions about Tracking And Solutions

What does Tracking And Solutions do?

A skill your agent uses for Ultralytics track mode, tracker YAML selection, persistent object IDs, and YOLO Solutions such as counting, heatmaps, speed, queue, region, similarity search, and…. Tracking And Solutions is an agent skill from VectorSpaceLab/AREX-Skill. Use for Ultralytics track mode, tracker YAML selection, persistent object IDs, and YOLO Solutions such as counting, heatmaps, speed, queue, region, similarity search, and Streamlit inference.

When should I use Tracking And Solutions?

Tracking And Solutions fits situations like: ultralytics track mode; tracker YAML selection; persistent object IDs; YOLO Solutions such as counting.

How do I install Tracking And Solutions in Claude Code?

Run `npx skills add VectorSpaceLab/AREX-Skill --skill tracking-and-solutions -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/ultralytics/sub-skills/tracking-and-solutions in VectorSpaceLab/AREX-Skill) into .claude/skills/tracking-and-solutions in your project. Claude Code loads it when a task matches its description.

How do I install Tracking And Solutions in Codex?

Run `npx skills add VectorSpaceLab/AREX-Skill --skill tracking-and-solutions -a codex`. Or copy the skill folder (skills/repositories/repo-skills/ultralytics/sub-skills/tracking-and-solutions in VectorSpaceLab/AREX-Skill) into .agents/skills/tracking-and-solutions in your project. Codex loads it when a task matches its description.

Can I use Tracking And Solutions in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add VectorSpaceLab/AREX-Skill --skill tracking-and-solutions -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tracking-and-solutions, .gemini/skills/tracking-and-solutions, .github/skills/tracking-and-solutions and .opencode/skills/tracking-and-solutions in your project.

What does Tracking And Solutions need to run?

Going by SKILL.md and its folder, Tracking And Solutions needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Tracking And Solutions access the network?

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.

Is Tracking And Solutions safe to install?

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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Tracking And Solutions use?

Tracking And Solutions is published under the AGPL-3.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tracking And Solutions use?

About 871 tokens (SKILL.md is roughly 3.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.7k tokens, read only when the agent opens those files.

What are the alternatives to Tracking And Solutions?

Skills that share tags, products or a category with Tracking And Solutions: Cookbook Aiml (databricks-solutions/databricks-apps-cookbook, 183 stars), Chroma Vector Database (Orchestra-Research/AI-Research-SKILLs, 13k stars), Codebase Management (giancarloerra/SocratiCode, 3.3k stars) and Hermes Memory Providers (mnemosyne-oss/mnemosyne, 3.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tracking And Solutions?

VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 330 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on September 3, 2026.

Source: VectorSpaceLab/AREX-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.