Documentation
CLI Reference
IWE Stats

IWE Stats

Generates comprehensive statistics about your knowledge graph.

Usage 

iwe stats [OPTIONS]

Options

  • -f, --format <FORMAT>: Output format (default: markdown)
    • markdown: Human-readable formatted statistics
    • csv: Machine-readable CSV format with per-document statistics

What it shows

The stats command provides detailed analytics across multiple dimensions:

Overview

  • Total documents in your knowledge base
  • Total nodes (all content elements)
  • Total paths through the graph

Document Statistics

  • Total sections/headers across all documents
  • Average sections per document
  • Top 10 documents by section count
  • Paragraph counts per document

Reference Statistics

  • Block references (embedded documents)
  • Inline references (wiki-links)
  • Total references count
  • Orphaned documents (no incoming references)
  • Leaf documents (no outgoing references)
  • Top 10 most referenced documents

Lines Statistics

  • Total lines across all documents
  • Average lines per document
  • Top 10 largest documents by line count

Words Statistics

  • Total words across all documents
  • Average words per document
  • Top 10 largest documents by word count

Structure Statistics

  • Root-level sections
  • Maximum and average path depth
  • Counts of bullet lists, ordered lists, code blocks, tables, and quotes

Network Analysis

  • Average references per document
  • Top 10 most connected documents (by total incoming + outgoing references)

Examples 

# Generate human-readable statistics (default)
iwe stats

# Export per-document statistics as CSV
iwe stats --format csv > stats.csv

# Analyze CSV data with standard tools
iwe stats -f csv | cut -d, -f1,2,3 | column -t -s,

Sample Markdown Output 

# Graph Statistics

## Overview

- **Total documents:** 39
- **Total nodes:** 1552
- **Total paths:** 302

## Document Statistics

- **Total sections:** 844
- **Average sections/doc:** 21.64

### Top Documents by Sections

1. **VS Code** (102 sections)
2. **Neovim** (89 sections)
3. **Extract Actions** (79 sections)
...

## Lines Statistics

- **Total lines:** 3404
- **Average lines/doc:** 87.28

### Top Documents by Lines

1. **Neovim** (429 lines)
2. **Extract Actions** (342 lines)
...

## Words Statistics

- **Total words:** 14204
- **Average words/doc:** 364.21

### Top Documents by Words

1. **Neovim** (1337 words)
2. **Extract Actions** (1200 words)
...

CSV Format Details

The CSV format provides per-document statistics with the following columns:

  • key: Document identifier/filename
  • title: Document title (first heading)
  • sections: Number of heading sections
  • paragraphs: Number of paragraph blocks
  • lines: Total line count
  • words: Total word count
  • incoming_block_refs: Block references pointing to this document
  • incoming_inline_refs: Inline wiki-links pointing to this document
  • total_incoming_refs: Total incoming references
  • outgoing_block_refs: Block references in this document
  • outgoing_inline_refs: Inline wiki-links from this document
  • total_connections: Total references (incoming + outgoing)
  • bullet_lists: Number of unordered lists
  • ordered_lists: Number of numbered lists
  • code_blocks: Number of code/raw blocks
  • tables: Number of tables
  • quotes: Number of quote blocks

Using CSV Output

The CSV format enables programmatic analysis and integration with data tools:

# Import into spreadsheet applications
iwe stats -f csv > knowledge-base-stats.csv

# Find most connected documents
iwe stats -f csv | tail -n +2 | sort -t, -k12 -nr | head -5

# Calculate total word count
iwe stats -f csv | tail -n +2 | cut -d, -f6 | paste -sd+ | bc

# Filter documents with many references
iwe stats -f csv | awk -F, '$9 > 5 {print $1, $2, $9}' OFS=,

# Generate reports with Python/pandas
import pandas as pd
df = pd.read_csv('stats.csv')
print(df.describe())
print(df.nlargest(10, 'total_connections'))
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