surprise-me

Original：🇺🇸 English
Translated

Analyze your reading history and tell you something surprising you don't know about yourself

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Sourcereadwiseio/readwise-skills
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NPX Install

npx skill4agent add readwiseio/readwise-skills surprise-me

Tags

Translated version includes tags in frontmatter
readwise-analysisreading-insightsdata-gatheringuser-behaviorcli-tools

SKILL.md Content

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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.

Readwise Access

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.

Process

1. Gather Data

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.

2. Analyze

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?

3. Deliver the Surprise

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

4. Go Deeper

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?"

Tone

  • 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