/surprise-me

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