Yolo Detection 2026

What it does

When your agent uses it

• Tasks that involve Computer vision

Example prompts

• “/yolo-detection-2026”

Requirements

• Python 3
• A Bash shell

Workflow steps

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

1. 1deploy.sh detects your hardware via env_config.HardwareEnv.detect()
2. 2Installs the matching requirements_{backend}.txt (e.g. CUDA → includes tensorrt)
3. 3Pre-converts the default model to the optimal format
4. 4At runtime, detect.py loads the cached optimized model automatically
5. 5Falls back to PyTorch if optimization fails

What it can do on your machine

Read from SKILL.md and the folder at commit 933dcc7. 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 2 files in scripts/ (Python, Batch and Shell), which the agent can run.

  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

Yolo Detection 2026 loads about 1.5k tokens when it runs. Until then it costs about 19 tokens; SKILL.md has 338 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~19

When it runs · the whole SKILL.md, loaded when a task matches

~1.5k

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

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 SharpAI/DeepCamera at commit 933dcc7, republished under its MIT licence (© SharpAI). 338 words, ~1,528 tokens.

name

yolo-detection-2026

description

YOLO 2026 — state-of-the-art real-time object detection

version

2.0.0

icon

assets/icon.png

entry

scripts/detect.py

deploy

deploy.sh

requirements.python

>=3.9

requirements.ultralytics

>=8.3.0

requirements.torch

>=2.4.0

requirements.platforms

linux, macos, windows

auto_start: true
model_size: nano
fps: 5

{"event": "perf_stats", "total_frames": 50, "timings_ms": {
  "inference": {"avg": 3.4, "p50": 3.2, "p95": 5.1},
  "postprocess": {"avg": 0.15, "p50": 0.12, "p95": 0.31},
  "total": {"avg": 3.6, "p50": 3.4, "p95": 5.5}
}}

{"event": "frame", "frame_id": 42, "camera_id": "front_door", "timestamp": "...", "frame_path": "/tmp/aegis_detection/frame_front_door.jpg", "width": 1920, "height": 1080}

{"event": "ready", "model": "yolo2026n", "device": "mps", "backend": "mps", "format": "coreml", "gpu": "Apple M3", "classes": 80, "fps": 5}
{"event": "detections", "frame_id": 42, "camera_id": "front_door", "timestamp": "...", "objects": [
  {"class": "person", "confidence": 0.92, "bbox": [100, 50, 300, 400]}
]}
{"event": "perf_stats", "total_frames": 50, "timings_ms": {"inference": {"avg": 3.4}}}
{"event": "error", "message": "...", "retriable": true}

{"command": "stop"}

./deploy.sh

© SharpAI, MIT. 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 13 other files (scripts) in skills/detection/yolo-detection-2026 of SharpAI/DeepCamera.

• SKILL.md
• config.yaml
• deploy.bat
• deploy.sh
• requirements.txt
• requirements_cpu.txt
• requirements_cuda.txt
• requirements_intel.txt
• requirements_mps.txt
• requirements_rocm.txt
• scripts/detect.py
• scripts/env_config.py
• yolo26n.onnx
• yolo26n_names.json

Open the folder on GitHubat commit 933dcc7