gh-stbenjam-claude-nine-plugins-goodreads/commands/stats.md

description

description
Show reading statistics (books per year/month, pages read, average rating, genre breakdown)

You are helping the user analyze their reading statistics from their Goodreads library.

Analysis to Perform

Use the analyze-goodreads-export skill to gather and analyze the following statistics:

1. Reading Velocity

Query books read in different time periods:

• Books read this year (use date_read.year == current_year)
• Books read last 30 days
• Books read last 90 days
• Break down by month for current year

Calculate:

• Books per month average (current year)
• Pages per month average
• Current reading pace vs yearly average

2. Page Statistics

Query all read books with page counts:

• Total pages read this year
• Total pages read all time
• Average pages per book
• Longest book read
• Shortest book read

3. Rating Analysis

Query all read books with ratings:

• Average rating given (your my_rating field)
• Average Goodreads rating of books read (average_rating field)
• Most common rating you give
• Distribution of ratings (how many 5-star, 4-star, etc.)

4. Author Statistics

Query all read books:

• Most read authors (count by author name)
• Total unique authors read

5. Series Statistics

Query all read books with series information:

• Books read that are part of series vs standalone
• Most read series
• Number of complete series finished

6. To-Be-Read Statistics

Query TBR list (where is_tbr is True):

• Total books in TBR
• Total pages in TBR
• Average Goodreads rating of TBR
• Oldest book in TBR (by date_added)
• Books added to TBR in last 30 days

Output Format

Present statistics in a clean, organized report:

# READING STATISTICS

## 📊 Reading Velocity
- **This Year**: X books (Y pages)
- **Last 30 Days**: X books (Y pages)
- **Average Pace**: X books/month, Y pages/month

### Monthly Breakdown (YYYY)
Jan: X books | Feb: X books | Mar: X books | etc.

## 📖 Page Statistics
- **Total Pages Read (All Time)**: X,XXX pages
- **Total Pages Read (This Year)**: X,XXX pages
- **Average Book Length**: XXX pages
- **Longest Book**: [Title] by [Author] (XXX pages)
- **Shortest Book**: [Title] by [Author] (XXX pages)

## ⭐ Rating Analysis
- **Your Average Rating**: X.X / 5
- **Goodreads Average of Books Read**: X.X / 5
- **Most Common Rating**: X stars

### Rating Distribution
★★★★★: XX books (XX%)
★★★★☆: XX books (XX%)
★★★☆☆: XX books (XX%)
★★☆☆☆: XX books (XX%)
★☆☆☆☆: XX books (XX%)

## ✍️ Author Statistics
- **Total Authors Read**: XX unique authors
- **Most Read Authors**:
  1. [Author Name]: X books
  2. [Author Name]: X books
  3. [Author Name]: X books

## 📚 Series Statistics
- **Books in Series**: XX books (XX% of total)
- **Standalone Books**: XX books (XX% of total)
- **Most Read Series**:
  1. [Series Name]: X books
  2. [Series Name]: X books

## 📋 To-Be-Read Statistics
- **Total TBR Books**: XXX books (X,XXX pages)
- **Average TBR Rating**: X.X / 5
- **Added Recently**: XX books in last 30 days
- **Oldest Unread**: [Title] (added X years/months ago)

## 🎯 Reading Insights
[Provide 2-3 interesting insights, such as:]
- You're on track to read XX books this year
- Your reading pace has [increased/decreased] compared to last year
- You tend to rate books higher/lower than Goodreads average
- You're reading more/fewer series books than standalone

Implementation

Write a Python script using goodreads_lib to:

1. Query all read books
2. Calculate statistics for each category
3. Format and display results with proper formatting

Use the Bash tool to run your Python script.

Important Notes

• Use date_read field to determine if/when book was read
• Calculate percentages and averages from the data
• Present large numbers with thousand separators for readability
• Compare current year to all-time averages where interesting
• Handle missing data gracefully (some books may not have all fields)
• Round floating point values to 2 decimal places for readability