Golden quote miner
从播客逐字稿、文章、演讲稿等文本中提取最具传播力和启发性的金句。触发条件:用户提到"金句"、"挖掘金句"、"找金句"、"提取金句"、"quote mining"、"golden quotes",或在播客/内容制作流程中需要精选引用语句时。From its SKILL.md
npx -y skills add carpo9984/GQXJ --skill golden-quote-minerAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 1 stars1 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.
SKILL.md
3.7 KB, ~1.4k tokens by cl100k_base, as published. Nobody here has run it
金句挖掘
从用户提供的文本中精准识别并提取最富有启发性、总结性和传播力的"金句"。所有提取必须 100% 忠于原文。
第一步:获取源文本
- 飞书链接 → 优先使用当前 AI 已连接的飞书工具读取;如果没有飞书权限,请用户导出文件、上传逐字稿或直接粘贴正文
- 直接粘贴 → 接收用户粘贴的文本
- 本地文件 → Read 读取
第二步:金句筛选标准
按以下四个维度严格判断一句话是否为金句:
- 观点精辟:一针见血地指出问题本质,引发深度思考
- 高度概括:用简短话语总结复杂概念或核心思想
- 表达独特:语言生动、比喻恰当,具有记忆点和传播潜力
- 情感共鸣:能触动人心,引发强烈情感共鸣
严格筛选规则:
- 每条金句必须至少同时满足两条及以上标准,宁缺毋滥
- 只满足一条的句子直接淘汰,不要因为"还不错"就降低门槛
- 如果某位说话人确实没有合格金句,可以缺位,不要强行凑数
第三步:提取金句
最重要规则:100% 原句提取
- 提取的句子必须是文本中的完整原话
- 绝对禁止任何形式的删减、修改、重组或意译
- 必须逐字逐句提取,即使原句在语法上不完美,也不得修改
- 当用户说"我要原句"时,严格对照原文逐字重新核对
首次提取
主动挑选 10-15 条最精彩的金句,优先选择同时满足多条筛选标准的句子。
必须为每条金句标注所属维度,格式为在句末加标注,如:(观点精辟 + 情感共鸣)。维度组合常见的包括:
- 观点精辟 + 高度概括 → 适合做标题、摘要
- 观点精辟 + 表达独特 → 适合做传播金句
- 表达独特 + 情感共鸣 → 适合做情绪钩子
响应追问
理解并执行用户的细化要求:
- "再为[某人]挑一些" → 聚焦该说话人
- "再多找几句" → 降低阈值,扩充到 20+ 条
- "找关于[主题]的金句" → 按主题筛选
- "我要原句" → 重新逐字核对原文
第四步:输出格式
基础输出(按说话人分组):
**[说话人姓名/身份]:**
1. (时间点) 完整的原句内容(维度A + 维度B)
2. (时间点) 完整的原句内容(维度A + 维度B)
**[另一位说话人姓名/身份]:**
1. (时间点) 完整的原句内容(维度A + 维度B)
进阶输出(按维度组合分类):当用户要求严格筛选或按标准分类时,用此格式:
### 观点精辟 + 高度概括
...该类金句
### 表达独特 + 情感共鸣
...该类金句
### 观点精辟 + 表达独特
...该类金句
每条金句末尾必须标注 (满足维度 + 满足维度),便于用户快速判断用途。
格式规则
- 如果原文有时间戳,必须标注时间点
- 如果原文标明说话人,必须注明身份;无法确定说话人时用"说话人A/说话人B"区分
- 如果没有时间戳,写
(--:--) - 保持输出格式清晰一致,按说话人分组
注意事项
- 不要输出分析、点评或推荐理由,只输出金句本身
- 不要对金句排序(除非用户要求),保持原文出现顺序
- 当用户指出有修改时,立即重新核对原文并提供准确的原句,不要辩解
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most sales audience skills give in ~1.4k tokens
Counted across 401 of the 401 authors here whose files we hold, read 2026-08-07
- Read product marketing context before asking questionsin 21 of 401, across 11 files
- Acknowledge competitor strengths honestlyin 18 of 401, across 7 files
- Start every page with a summaryin 15 of 401, across 4 files
- Use a single, low-friction call to actionin 15 of 401, across 7 files
- Create a single source of truth for each competitorin 14 of 401, across 3 files
- Make each follow-up email add new valuein 11 of 401, across 5 files
- Cut any sentence that does not drive a replyin 10 of 401, across 4 files
- Tie personalization directly to the problemin 10 of 401, across 4 files
- Write paragraph comparisons for each dimensionin 9 of 401, across 3 files
- Link between related competitor pagesin 9 of 401, across 3 files
- Keep subject lines short and lowercasein 9 of 401, across 3 files
- Define ideal customer profile from top customersin 9 of 401, across 3 files
Said here and by no other author read
- extract quotes verbatim
- select 10 to 15 best quotes initially
- require each quote to meet two criteria
- append matched criteria tags to each quote
- group output by speaker
- include timestamps if present
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.