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love254443233

万相 2.6 生成微信公众号封面图

by love254443233 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
90
Downloads
1
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install wan26-text-to-image
Description
使用阿里云万相 2.6 模型生成微信公众号封面图和技术架构设计图
Usage Guidance
This skill appears to implement the advertised image-generation features, but there are two practical concerns to weigh before installing: (1) the registry metadata omits that you must provide an API key—the code expects DASHSCOPE_API_KEY (and will also accept QWEN_API_KEY / ALIYUN_DASHSCOPE_API_KEY); verify the skill metadata is updated so you understand what secrets are required; (2) the runtime will load shared env files (OPENCLAW_ENV_FILE, ~/.openclaw/.env, ~/.workbuddy/.env) to locate keys. If those files contain credentials for other services, the skill could read them. Recommended actions: inspect the code locally (you already have it), provide the API key via a dedicated .env in the skill folder or explicit --api-key when invoking, avoid placing unrelated secrets in shared ~/.openclaw/.env or ~/.workbuddy/.env, and run the tool in a sandboxed environment if you cannot fully trust the author. If you need higher assurance, ask the maintainer to update registry metadata to declare DASHSCOPE_API_KEY as a required env var and to avoid loading unrelated shared env files by default.
Capability Analysis
Type: OpenClaw Skill Name: wan26-text-to-image Version: 1.0.0 The skill bundle is a legitimate tool for generating images using Alibaba's Wanxiang 2.6 API. It follows security best practices by managing API keys through local .env files with restricted permissions (chmod 600) and explicitly avoids printing sensitive credentials to the console in setup.sh and config.py. The core logic in wan26_generator.py is transparent, using the official dashscope SDK and standard requests library to download generated images to a designated local directory (~/WorkBuddy/), with no evidence of data exfiltration, malicious execution, or harmful prompt injection.
Capability Assessment
Purpose & Capability
The code and SKILL.md match the stated purpose (generate WeChat cover images, tech diagrams, article images using Aliyun Wan/Dashtscope). Required Python deps (dashscope, requests) are appropriate. However, the registry metadata claims no required env vars while the skill clearly needs an API key (DASHSCOPE_API_KEY / QWEN_API_KEY / ALIYUN_DASHSCOPE_API_KEY), which is an inconsistency.
Instruction Scope
SKILL.md and code instruct the agent to load environment variables from multiple locations in order (OPENCLAW_ENV_FILE, local .env, ~/.openclaw/.env, ~/.workbuddy/.env). That behavior goes beyond just reading a single service key and may read shared config files used by other skills/platform components, increasing the risk of unintended access to other secrets. Other runtime behavior (creating local .env, saving images under ~/WorkBuddy/<skill>) is coherent with the stated purpose.
Install Mechanism
No risky remote install steps or arbitrary downloads are present; dependencies are normal Python packages listed in requirements.txt. There is no install spec in the registry (instruction-only), and bundled scripts are simple local helpers (setup.sh, config.py).
Credentials
The skill requires an API key for Aliyun Dashscope but the registry metadata did not declare any required env vars—this omission is misleading. The skill also accepts multiple env var names and will load several env files (including ~/.openclaw/.env and ~/.workbuddy/.env), which could expose unrelated credentials if those files contain other secrets. Requesting a single service API key would be proportionate; reading shared env files is broader than necessary.
Persistence & Privilege
always:false and no evidence the skill modifies other skills or system-wide agent settings. It writes a local .env in its own directory and saves images under a user WorkBuddy directory—reasonable for functionality. Still, users should note files are created under the user home.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install wan26-text-to-image
  3. After installation, invoke the skill by name or use /wan26-text-to-image
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- 首个版本发布,支持使用阿里云万相 2.6 模型生成微信公众号封面图、技术架构设计图和文章配图 - 提供三大命令:generate_wx_cover、generate_tech_diagram、generate_article_images - 新增多种参数支持,含图片风格、尺寸与 API Key 传递,可灵活调用 - 支持本地 .env 多路径自动加载与与 OpenClaw 等工具共用密钥配置 - 输出图片规格明确,支持机器可读 JSON-only 输出模式 - 强调安全合规实践,明确避免密钥泄露
Metadata
Slug wan26-text-to-image
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is 万相 2.6 生成微信公众号封面图?

使用阿里云万相 2.6 模型生成微信公众号封面图和技术架构设计图. It is an AI Agent Skill for Claude Code / OpenClaw, with 90 downloads so far.

How do I install 万相 2.6 生成微信公众号封面图?

Run "/install wan26-text-to-image" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is 万相 2.6 生成微信公众号封面图 free?

Yes, 万相 2.6 生成微信公众号封面图 is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does 万相 2.6 生成微信公众号封面图 support?

万相 2.6 生成微信公众号封面图 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created 万相 2.6 生成微信公众号封面图?

It is built and maintained by love254443233 (@love254443233); the current version is v1.0.0.

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