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aliyun-qvq

aliyun-qvq

github.com/cinienceData & databases39657 installsUpdated 11w ago
Repository

About aliyun-qvq

aliyun-qvq is a skill for preparing requests to Alibaba Cloud Model Studio’s QVQ visual reasoning models. It targets tasks that require multi-step reasoning grounded in screenshots, diagrams, or charts.

Key features

  1. 01Prepares QVQ request files
  2. 02Uses qvq-plus or qvq-max
  3. 03Targets visual multi-step reasoning

Use cases

  1. 01Reasoning about math screenshots
  2. 02Analyzing diagrams and charts

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/cinience/alicloud-skills --skill aliyun-qvq

After installing, type/aliyun-qvqin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
sources.md
scripts/
prepare_qvq_request.py

Details

From the project README

Category: provider

Model Studio QVQ Visual Reasoning

Validation

mkdir -p output/aliyun-qvq
python -m py_compile skills/ai/multimodal/aliyun-qvq/scripts/prepare_qvq_request.py && echo "py_compile_ok" > output/aliyun-qvq/validate.txt

Pass criteria: command exits 0 and output/aliyun-qvq/validate.txt is generated.

Critical model names

Use one of these exact model strings:

  • qvq-plus
  • qvq-max

Typical use

  • Mathematical reasoning from screenshots
  • Diagram and chart reasoning
  • Visually grounded multi-step problem solving

Quick start

python skills/ai/multimodal/aliyun-qvq/scripts/prepare_qvq_request.py \
  --output output/aliyun-qvq/request.json

Notes

  • Use skills/ai/multimodal/aliyun-qwen-vl/ for standard image understanding.
  • Use QVQ when the task explicitly needs stronger reasoning over visual evidence.

References

  • references/sources.md

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