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Install in OpenClaw
/install rendshot-xiaohongshu
Description
Create high-performing Xiaohongshu (Little Red Book / RED) cover images and content graphics. Use when the user mentions: '小红书', 'xiaohongshu', 'RED', '种草',...
Usage Guidance
This skill appears coherent and low-risk as packaged, but before installing consider: 1) Verify your platform provides the listed runtime functions (generate_image, list_templates, create_template) and whether calls incur usage costs or require a separate API key managed by the platform. 2) Confirm how generated images, user-supplied photos, and template data are stored/retained by the backend (privacy/retention). 3) Review prompts and generated copy for sensitive, promotional, or copyrighted content before publishing to Xiaohongshu. 4) If you integrate with an external Rendshot service outside your control, review that service's reputation and access/credential requirements. If you need me to check for hidden network endpoints or credential usage, provide an install spec or code files for further review.
Capability Analysis
Type: OpenClaw Skill
Name: rendshot-xiaohongshu
Version: 1.0.0
The skill bundle is a legitimate tool designed to generate optimized cover images for the Xiaohongshu platform. It provides a structured workflow in SKILL.md and comprehensive reference materials (algorithm.md, design-style.md) to guide the AI agent in creating high-quality marketing content. The code uses specific image generation tools (generate_image, list_templates) consistent with its stated purpose, and there is no evidence of data exfiltration, malicious execution, or harmful prompt injection.
Capability Assessment
Purpose & Capability
The name/description match the instructions and reference files: the skill guides prompt and template-based image generation for Xiaohongshu using platform functions (list_templates, get_template, generate_image, create_template). It does not request unrelated services or credentials.
Instruction Scope
SKILL.md confines runtime actions to gathering user/context info, selecting design patterns from local references, and calling the declared image/template generation functions. It does not instruct reading unrelated system files, environment variables, or exfiltrating data.
Install Mechanism
No install spec or code files are present; this is instruction-only, so nothing is written to disk or downloaded at install time.
Credentials
No environment variables, credentials, or config paths are requested. The requirements are minimal and appropriate for an instruction-only design-and-generation skill.
Persistence & Privilege
The skill is not forced-always, and does not request elevated privileges or modifications to other skills. Normal autonomous invocation is allowed (platform default) but not unusual or excessive here.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install rendshot-xiaohongshu - After installation, invoke the skill by name or use
/rendshot-xiaohongshu - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: Xiaohongshu algorithm, design styles, template recommendations
Metadata
Frequently Asked Questions
What is Xiaohongshu Image Generator?
Create high-performing Xiaohongshu (Little Red Book / RED) cover images and content graphics. Use when the user mentions: '小红书', 'xiaohongshu', 'RED', '种草',... It is an AI Agent Skill for Claude Code / OpenClaw, with 82 downloads so far.
How do I install Xiaohongshu Image Generator?
Run "/install rendshot-xiaohongshu" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Xiaohongshu Image Generator free?
Yes, Xiaohongshu Image Generator is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Xiaohongshu Image Generator support?
Xiaohongshu Image Generator is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Xiaohongshu Image Generator?
It is built and maintained by Martian (@zoohero500); the current version is v1.0.0.
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