alicloud-ai-multimodal-qwen-vl

cinience/alicloud-skills · updated Apr 8, 2026

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$npx skills add https://github.com/cinience/alicloud-skills --skill alicloud-ai-multimodal-qwen-vl
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summary

Category: provider

skill.md

Category: provider

Model Studio Qwen VL (Image Understanding)

Validation

mkdir -p output/alicloud-ai-multimodal-qwen-vl
python -m py_compile skills/ai/multimodal/alicloud-ai-multimodal-qwen-vl/scripts/analyze_image.py && echo "py_compile_ok" > output/alicloud-ai-multimodal-qwen-vl/validate.txt

Pass criteria: command exits 0 and output/alicloud-ai-multimodal-qwen-vl/validate.txt is generated.

Output And Evidence

  • Save raw model responses and normalized extraction results to output/alicloud-ai-multimodal-qwen-vl/.
  • Include input image reference and prompt for traceability.

Use Qwen VL models for image input + text output understanding tasks via DashScope compatible-mode API.

Prerequisites

  • Install dependencies (recommended in a venv):
python3 -m venv .venv
. .venv/bin/activate
python -m pip install requests
  • Set DASHSCOPE_API_KEY in environment, or add dashscope_api_key to ~/.alibabacloud/credentials.

Critical model names

Prefer the Qwen3 VL family:

  • qwen3-vl-plus
  • qwen3-vl-flash

When you need explicit "latest" routing or reproducible snapshots, use supported aliases/snapshots from the official model list, such as:

  • qwen3-vl-plus-latest
  • qwen3-vl-plus-2025-12-19
  • qwen3-vl-flash-2026-01-22
  • qwen3-vl-flash-latest

Legacy names still seen in some workloads:

  • qwen-vl-max-latest
  • qwen-vl-plus-latest

For OCR-specialized extraction, prefer skills/ai/multimodal/alicloud-ai-multimodal-qwen-ocr/ instead of using the general VL skill.

Normalized interface (multimodal.chat)

Request

  • prompt (string, required): user question/instruction about image.
  • image (string, required): HTTPS URL, local path, or data: URL.
  • model (string, optional): default qwen3-vl-plus.
  • max_tokens (int, optional): default 512.
  • temperature (float, optional): default 0.2.
  • detail (string, optional): auto/low/high, default auto.
  • json_mode (bool, optional): return JSON-only response when possible.
  • schema (object, optional): JSON Schema for structured extraction.
  • max_retries (int, optional): retry count for 429/5xx, default 2.
  • retry_backoff_s (float, optional): exponential backoff base seconds, default 1.5.

Response

  • text (string): primary model answer.
  • model (string): model actually used.
  • usage (object): token usage if returned by backend.

Quickstart

python skills/ai/multimodal/alicloud-ai-multimodal-qwen-vl/scripts/analyze_image.py \
  --request '{"prompt":"Summarize the main content in this image","image":"https://example.com/demo.jpg"}' \
  --print-response

Using local image:

python skills/ai/multimodal/alicloud-ai-multimodal-qwen-vl/scripts/analyze_image.py \
  --request '{"prompt":"Extract key information from the image","image":"./samples/invoice.png","model":"qwen3-vl-plus"}' \
  --print-response

Structured extraction (JSON mode):

python skills/ai/multimodal/alicloud-ai-multimodal-qwen-vl/scripts/analyze_image.py \
  --request '{"prompt":"Extract fields: title, amount, date","image":"./samples/invoice.png"}' \
  --json-mode \
  --print-response

Structured extraction (JSON Schema):

python skills/ai/multimodal/alicloud-ai-multimodal-qwen-vl/scripts/analyze_image.py \
  --request '{"prompt":"Extract invoice fields","image":"./samples/invoice.png"}' \
  --schema skills/ai/multimodal/alicloud-ai-multimodal-qwen-vl/references/examples/invoice.schema.json \
  --print-response

cURL (compatible mode)

curl -sS https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model":"qwen3-vl-plus",
    "messages":[
      {
        "role":"user",
        "content":[
          {"type":"image_url","image_url":{"url":"https://example.com/demo.jpg"}},
          {"type":"text","text":"Describe this image and list executable actions"}
        ]
      }
    ],
    "max_tokens":512,
    "temperature":0.2
  }'

Output location

  • If --output is set, JSON response is saved to that file.
  • Default output dir convention: output/alicloud-ai-multimodal-qwen-vl/.

Smoke test

python tests/ai/multimodal/alicloud-ai-multimodal-qwen-vl-test/scripts/smoke_test_qwen_vl.py \
  --image ./tmp/vl_test_cat.png

Error handling

Error Likely cause Action
401/403 Missing or invalid key Check DASHSCOPE_API_KEY and account permissions.
400 Invalid request schema or unsupported image source Validate messages content and image URL/path format.
429 Rate limit Retry with exponential backoff and lower concurrency.
5xx Temporary backend issue Retry with backoff and idempotent request design.

Operational guidance

  • For stable production behavior, pin snapshot model IDs instead of pure -latest.
  • Compress very large images before upload to reduce latency and cost.
  • Add explicit extraction constraints in prompt (fields, JSON shape, language).
  • For OCR-like output, ask for confidence notes and unresolved text markers.

Workflow

  1. Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.
  2. Run one minimal read-only query first to verify connectivity and permissions.
  3. Execute the target operation with explicit parameters and bounded scope.
  4. Verify results and save output/evidence files.

References

  • Source list: references/sources.md
  • API notes: references/api_reference.md
how to use alicloud-ai-multimodal-qwen-vl

How to use alicloud-ai-multimodal-qwen-vl on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add alicloud-ai-multimodal-qwen-vl
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/cinience/alicloud-skills --skill alicloud-ai-multimodal-qwen-vl

The skills CLI fetches alicloud-ai-multimodal-qwen-vl from GitHub repository cinience/alicloud-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/alicloud-ai-multimodal-qwen-vl

Reload or restart Cursor to activate alicloud-ai-multimodal-qwen-vl. Access the skill through slash commands (e.g., /alicloud-ai-multimodal-qwen-vl) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.470 reviews
  • Noah Kim· Dec 28, 2024

    alicloud-ai-multimodal-qwen-vl has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Li Johnson· Dec 28, 2024

    Solid pick for teams standardizing on skills: alicloud-ai-multimodal-qwen-vl is focused, and the summary matches what you get after install.

  • Nia Yang· Dec 24, 2024

    Useful defaults in alicloud-ai-multimodal-qwen-vl — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Luis Park· Dec 20, 2024

    alicloud-ai-multimodal-qwen-vl has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Chaitanya Patil· Dec 16, 2024

    alicloud-ai-multimodal-qwen-vl reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Hassan Huang· Dec 4, 2024

    alicloud-ai-multimodal-qwen-vl is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Carlos Anderson· Nov 19, 2024

    alicloud-ai-multimodal-qwen-vl fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Chen Okafor· Nov 19, 2024

    Keeps context tight: alicloud-ai-multimodal-qwen-vl is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Kaira Sanchez· Nov 19, 2024

    We added alicloud-ai-multimodal-qwen-vl from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Li Smith· Nov 15, 2024

    Registry listing for alicloud-ai-multimodal-qwen-vl matched our evaluation — installs cleanly and behaves as described in the markdown.

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