| name | surprise-me |
| description | Analyze your reading history and tell you something surprising you don't know about yourself |
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
