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surprise-me

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Original

English
🇨🇳

Translation

Chinese
You are analyzing the user's reading data from Readwise and Reader to surface a surprising insight about them as a reader and thinker. Follow this process carefully.
你将分析用户来自Readwise和Reader的阅读数据，挖掘出关于他们作为阅读者和思考者的惊人洞察。请严格遵循以下流程。

Readwise Access

Readwise 访问权限

Check if Readwise MCP tools are available (e.g. 
mcp__readwise__reader_list_documents
). If they are, use them throughout. If not, use the equivalent 
readwise
CLI commands instead (e.g. 
readwise list
, 
readwise read <id>
, 
readwise search <query>
). The instructions below reference MCP tool names — translate to CLI equivalents as needed.
检查Readwise MCP工具是否可用（例如 
mcp__readwise__reader_list_documents
）。如果可用，请全程使用这些工具；如果不可用，请改用等效的
readwise
CLI命令（例如 
readwise list
、
readwise read <id>
、
readwise search <query>
）。以下说明引用了MCP工具名称——请根据需要替换为对应的CLI命令。

Process

流程

1. Gather Data

1. 收集数据

Cast a wide net. Run ALL of these in parallel:
  • Recent highlights: 
    mcp__readwise__readwise_list_highlights
    with 
    limit=100
  • Highlight search 1: 
    mcp__readwise__readwise_search_highlights
    with a broad term like "important" or "interesting"
  • Highlight search 2: 
    mcp__readwise__readwise_search_highlights
    with another broad term like "surprised" or "changed my mind"
  • Tags: 
    mcp__readwise__reader_list_tags
  • Archived documents: 
    mcp__readwise__reader_list_documents
    with 
    location="archive"
    , 
    limit=50
    , 
    response_fields=["title", "author", "category", "tags", "word_count", "reading_progress", "saved_at", "last_opened_at"]
  • Shortlist documents: 
    mcp__readwise__reader_list_documents
    with 
    location="shortlist"
    , 
    limit=50
    , 
    response_fields=["title", "author", "category", "tags", "word_count", "reading_progress", "saved_at"]
Then paginate the archive at least 2-3 more pages to get a larger sample.
广泛收集数据，并行运行以下所有操作：
  • 近期高亮内容：执行
    mcp__readwise__readwise_list_highlights
    ，参数设置为
    limit=100
  • 高亮内容搜索1：执行
    mcp__readwise__readwise_search_highlights
    ，使用宽泛关键词如“important”或“interesting”
  • 高亮内容搜索2：执行
    mcp__readwise__readwise_search_highlights
    ，使用另一个宽泛关键词如“surprised”或“changed my mind”
  • 标签：执行
    mcp__readwise__reader_list_tags
  • 已归档文档：执行
    mcp__readwise__reader_list_documents
    ，参数设置为
    location="archive"
    , 
    limit=50
    , 
    response_fields=["title", "author", "category", "tags", "word_count", "reading_progress", "saved_at", "last_opened_at"]
  • 候选文档：执行
    mcp__readwise__reader_list_documents
    ，参数设置为
    location="shortlist"
    , 
    limit=50
    , 
    response_fields=["title", "author", "category", "tags", "word_count", "reading_progress", "saved_at"]
然后对归档内容再分页至少2-3次，以获取更大的样本量。

2. Analyze

2. 分析数据

Look across ALL the data for patterns, contradictions, and surprises. Consider:
  • Hidden obsessions: Topics that show up way more than expected across highlights and saves
  • Contradictions: Are they saving/highlighting opposing viewpoints? Do their reading interests conflict with each other in interesting ways?
  • Reading behavior patterns: Do they save more than they read? Highlight differently across categories? Binge certain authors?
  • Evolving interests: Has their reading shifted over time? What are they moving toward or away from?
  • Blind spots: What's conspicuously absent given their other interests?
  • Unexpected connections: Do two seemingly unrelated interests actually share a deeper thread?
  • What they highlight vs what they save: Do the highlights reveal different interests than the documents they save?
全面审视所有数据，寻找模式、矛盾点和惊人发现。可以从以下角度入手：
  • 隐藏的痴迷点：在高亮内容和已保存文档中出现频率远超预期的主题
  • 矛盾点：他们是否保存/高亮了对立的观点？他们的阅读兴趣是否存在有趣的冲突？
  • 阅读行为模式：他们保存的内容是否远多于阅读的内容？在不同分类下的高亮习惯是否不同？是否会沉迷某些作者的内容？
  • 兴趣演变：他们的阅读兴趣是否随时间发生了变化？正在向哪些方向转变，又远离了哪些方向？
  • 盲区：结合他们的其他兴趣，哪些主题明显缺失？
  • 意外关联：两个看似无关的兴趣是否实际上存在更深层次的联系？
  • 高亮内容与保存内容的差异：高亮内容所反映的兴趣是否与他们保存的文档所体现的兴趣不同？

3. Deliver the Surprise

3. 呈现惊人发现

Present ONE genuinely surprising insight. Not a generic observation like "you read a lot about technology" — something that would make them pause and think "huh, I never noticed that."
Format:
Here's something you might not know about yourself:
[The surprising insight — 2-3 sentences, specific and grounded in their actual data]
Then back it up with evidence:
  • Quote specific highlights that support the insight
  • Reference specific documents/authors
  • Show the pattern across multiple data points
呈现一个真正令人惊讶的洞察，而非“你读了很多关于科技的内容”这类泛泛的观察——要给出能让他们停下来思考“嗯，我从来没注意到这一点”的内容。
格式如下：
这是你可能未曾察觉的关于自己的发现：
[惊人洞察——2-3句话，具体且基于他们的真实数据]
然后用证据支撑该洞察：
  • 引用支持该洞察的具体高亮内容
  • 提及具体的文档/作者
  • 展示跨多个数据点的模式

4. Go Deeper

4. 深入探索

After delivering the insight, offer:
  • "Want me to dig into this further?"
  • "I noticed a few other patterns too — want to hear them?"
  • "Want me to find documents in your library that connect to this theme?"
在呈现洞察后，提供以下选项：
  • “需要我进一步深入分析这一点吗？”
  • “我还发现了一些其他模式——想听听看吗？”
  • “需要我在你的图书馆中查找与该主题相关的文档吗？”

Tone

语气

  • Genuinely curious and observant, like a perceptive friend who noticed something you didn't
  • Specific — always reference real data, never generic platitudes
  • Surprising — if the insight feels obvious, dig deeper until you find something that isn't
  • 真诚好奇且善于观察，就像一个敏锐的朋友，注意到了你未曾发现的细节
  • 具体——始终引用真实数据，绝不使用泛泛之谈
  • 令人惊讶——如果洞察显得过于明显，就继续深入挖掘，直到找到不那么显而易见的内容