agentsclimarketplace

Value judge

Skill unix2dos/skills/value-judge

My personal collection of handcrafted AI agent skills — original prompting modules for code quality, knowledge exploration, and daily productivity.

Install
npx -y skills add unix2dos/skills --skill value-judge

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Only invoke when explicitly requested via "值不值得看"、"评估打分"、"@value-judge" or "evaluate value". Do NOT auto-trigger.

SKILL.md

2.7 KB, as published. Nobody here has run it

价值判断与打分

对书籍、文章、GitHub 项目等内容进行多维度价值评分,输出结构化的评估报告。

工作流程

  1. 获取内容:从 URL 抓取或直接接收用户提供的内容
  2. 识别类型:根据 URL 特征或内容特点判断对象类型
  3. 加载维度:查阅 dimensions.md 获取该类型的评分维度
  4. 生成报告:按模板输出完整评估报告

对象类型识别

类型识别特征
📚 书籍douban.com/subjectgoodreads.com、书名+作者
📝 文章博客链接、medium.comzhihu.com、微信公众号
🐙 GitHub项目github.com/{owner}/{repo}
🎬 视频/课程youtube.combilibili.com、课程平台
🔧 工具/产品产品官网、producthunt.com
📄 论文arxiv.org、PDF 论文内容

无法识别时:提示用户明确指定类型。

输出格式

# 价值评估报告:《{标题}》

> **类型**:{对象类型} | **评估时间**:YYYY-MM-DD

## 📊 总分:{分数}/100

## 🎯 快速结论

| 项目 | 内容 |
|------|------|
| 一句话总结 | {概要} |
| 推荐指数 | ⭐⭐⭐⭐☆({N}/5)|
| 适合人群 | {目标受众} |

## 📈 维度评分

| 维度 | 分数 | 说明 |
|------|------|------|
| {维度1} | {分数}/100 | {评价} |
| {维度2} | {分数}/100 | {评价} |
| ... | ... | ... |

## 📝 详细评价

### ✅ 优点
- {优点1}
- {优点2}

### ⚠️ 不足
- {不足1}
- {不足2}

### 💡 建议
- {建议1}
- {建议2}

评分规则

  • 总分计算:各维度分数的加权平均(默认等权重)
  • 分数范围:1-100 分
  • 推荐指数映射
    • 90-100 → ⭐⭐⭐⭐⭐(5/5)强烈推荐
    • 75-89 → ⭐⭐⭐⭐☆(4/5)推荐
    • 60-74 → ⭐⭐⭐☆☆(3/5)一般
    • 40-59 → ⭐⭐☆☆☆(2/5)不推荐
    • 1-39 → ⭐☆☆☆☆(1/5)避坑

错误处理

场景处理方式
URL 无法访问报错:「无法访问该 URL,请检查链接或手动提供内容」
无法识别类型报错:「无法自动识别内容类型,请指定类型(书籍/文章/项目/视频/工具/论文)」
内容信息不足提示:「当前信息有限,建议补充完整内容以获得更准确的评估」

语言

所有输出固定使用中文

参考资料

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.