Object Detection Best Practices
Guides the agent on object detection architectures, training recipes, and COCO/VOC benchmarks.
- Repository
- aiming-lab/AutoResearchClaw
- Stars
- 14,802
- Licence
- MIT
- Files
- 1 file
What it does
This is a reference guide that teaches an AI agent the standard vocabulary and practices for object detection, the computer vision task of finding and labeling objects in images. Once installed, when a research or coding task involves COCO, Pascal VOC, or detectors like YOLO, DETR, or Faster R-CNN, the agent draws on these notes: which architecture families exist, a common training recipe (pre-trained backbones, multi-scale training, FPN, focal loss), IoU thresholds for evaluation, and typical reported benchmark scores. It is written as guidance only; it does not add tools or run anything.
Great for
- Researchers or students who want an agent to frame an object detection experiment with standard practices
- Developers choosing between one-stage, two-stage, and transformer detectors
- Anyone who wants a quick reminder of typical COCO and VOC benchmark numbers
Skip it if
- Production deployment or exact benchmark claims: the listed mAP figures are approximate and the file gives no sources beyond two paper references, so they should be verified against the original papers.
- Non-detection vision tasks such as classification or segmentation, which the guidance does not cover.
Try asking
- “Suggest a training recipe for fine-tuning YOLOv8 on a custom dataset in COCO format”
- “Explain the difference between one-stage and two-stage detectors for my project write-up”
- “What mAP should I expect from Faster R-CNN on COCO val2017?”
- “Review my detection evaluation code to confirm I use the right IoU thresholds for mAP50 and mAP50:95”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 1 original files, the MIT licence and an attribution note.
cv-detection.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip cv-detection.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip cv-detection.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Ask for specific guidance, such as a named architecture or dataset, so the agent applies the relevant section rather than general advice.
- Verify any benchmark numbers the agent quotes against the original papers or official leaderboards before using them in publications.
What's inside
- SKILL.md
Redistributed unmodified from aiming-lab/AutoResearchClaw under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.