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tobewin

Skill Recommender Pro

by ToBeWin · GitHub ↗ · v1.0.2 · MIT-0
cross-platform ✓ Security Clean
143
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0
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0
Active Installs
3
Versions
Install in OpenClaw
/install skill-recommender-pro
Description
Intelligent skill recommendations for OpenClaw. Analyzes installed skills using rule-based filtering and pattern matching. Suggests complementary skills, alt...
Usage Guidance
This skill appears coherent and focused: it uses the clawhub CLI and small Python snippets to inspect installed skills and search the registry, and it does not request secrets or install additional software. Before installing, verify you trust the clawhub binary on your system (the skill will invoke it), and remember recommendations produced may point you to other skills — inspect those target skills before installing. If you want further assurance, paste the output of `clawhub list` or run the SKILL.md's example commands locally to see what the recommender would do in your environment.
Capability Analysis
Type: OpenClaw Skill Name: skill-recommender-pro Version: 1.0.2 The skill-recommender-pro bundle is a legitimate tool designed to analyze a user's installed OpenClaw skills and suggest complementary or missing ones. It uses standard CLI commands (clawhub list/search/inspect) and straightforward Python scripts to categorize skills and generate reports, with no evidence of data exfiltration, malicious execution, or prompt injection.
Capability Assessment
Purpose & Capability
Name/description match the runtime instructions: the skill enumerates installed skills (clawhub list), searches the registry (clawhub search), and applies simple rules/keyword matching to produce recommendations. Requiring python3 and invoking clawhub is proportional to this purpose.
Instruction Scope
Instructions are focused on listing/searching skills and performing local analysis with small inline Python snippets. They do run subprocesses (clawhub list/search) and print included file contents for review; this is appropriate for a recommender but means the skill can read the local skill list and invoke clawhub. No instructions read unrelated system files or environment variables.
Install Mechanism
No install spec and no code files — instruction-only skill. Nothing is downloaded or written to disk by the skill itself.
Credentials
No environment variables, credentials, or config paths are requested. The skill only depends on the python3 binary and the clawhub CLI, which are relevant to its function.
Persistence & Privilege
always is false and the skill does not request permanent presence or elevated privileges. It does not modify other skills or system-wide settings in its instructions.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install skill-recommender-pro
  3. After installation, invoke the skill by name or use /skill-recommender-pro
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.2
修复安全扫描问题:移除curl依赖,明确语义分析由agent执行,不读取config文件
v1.0.1
AI驱动的Skill推荐:规则+LLM混合分析,智能互补推荐,多语言支持
v1.0.0
AI驱动的Skill推荐
Metadata
Slug skill-recommender-pro
Version 1.0.2
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 3
Frequently Asked Questions

What is Skill Recommender Pro?

Intelligent skill recommendations for OpenClaw. Analyzes installed skills using rule-based filtering and pattern matching. Suggests complementary skills, alt... It is an AI Agent Skill for Claude Code / OpenClaw, with 143 downloads so far.

How do I install Skill Recommender Pro?

Run "/install skill-recommender-pro" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Skill Recommender Pro free?

Yes, Skill Recommender Pro is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Skill Recommender Pro support?

Skill Recommender Pro is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Skill Recommender Pro?

It is built and maintained by ToBeWin (@tobewin); the current version is v1.0.2.

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