What is aliyun-qwen-vl?

A guide for using Alibaba Cloud Model Studio's Qwen VL models, which analyze images and return text.

Use it to build image question-answering, visual analysis, OCR-like extraction, chart reading, table reading, and screenshot-understanding workflows.

It provides a defined way to send images for visual questions, text extraction, chart or table reading, and screenshot understanding.

aliyun-qwen-vl — Skill for Codex by cinience

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/cinience/alicloud-skills

agentmods

npx agentmods add skills/cinience/alicloud-skills/aliyun-qwen-vl

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/cinience/alicloud-skills/aliyun-qwen-vl/github.svg)](https://agentmods.dev/skills/cinience/alicloud-skills/aliyun-qwen-vl)

Your own site

<a href="https://agentmods.dev/skills/cinience/alicloud-skills/aliyun-qwen-vl"><img src="https://agentmods.dev/badge/skills/cinience/alicloud-skills/aliyun-qwen-vl/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/cinience/alicloud-skills/aliyun-qwen-vl"><img src="https://agentmods.dev/badge/skills/cinience/alicloud-skills/aliyun-qwen-vl.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,504 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Rogue Agent · line 14
Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.

Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
medium Data Exfiltration · line 112
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00061	$0.01504
Opus 5	$0.00030	$0.00752
Sonnet 5	$0.00012	$0.00301
Haiku 4.5	$0.00006	$0.00150

Measured 12d ago against content hash bf6d82b52d05, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

aliyun-qwen-vl scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/analyze_image.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -sS https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions \

skills/ai/multimodal/aliyun-qwen-vl/SKILL.md · 173 lines

How it starts

The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Category: provider

Model Studio Qwen VL (Image Understanding)

Validation

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

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

Output And Evidence

Save raw model responses and normalized extraction results to output/aliyun-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/aliyun-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.

Read the full file on GitHub · 173 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

12d ago First seen · 173 lines · 61 tokens per session scan A bf6d82b52d05

Subscribe to this mod's changes

aliyun-qwen-vl is a skill published in the GitHub repository cinience/alicloud-skills (396 stars, last pushed 1mo ago), licensed MIT. It adds 61 tokens to every session and 1,504 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Data and AI

agent-platform-rag-engine-management

Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…

google/skills · 85 tokens

agent-platform-model-registry

Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.

google/skills · 60 tokens

foundry-config-setup

Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.

microsoft/agent-framework · 65 tokens

google-cloud-solution-agentic-analytics-spark-knowledge-catalog

Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…

google/skills · 138 tokens

training-check

Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.

wanshuiyin/Auto-claude-code-research-in-sleep · 35 tokens

nemo-automodel-launcher-config

Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.

NVIDIA/skills · 30 tokens

aliyun-qwen-vl