tokei: Code Statistics Analysis

Always invoke tokei skill for code statistics - do not execute bash commands directly.

Use tokei for fast, accurate code statistics across multiple languages and projects.

Default Strategy

Invoke tokei skill for analyzing code statistics by language. Use when understanding project composition, measuring change impact before refactoring, or generating CI/CD metrics.

Common workflow: tokei skill → other skills (fd, jq, yq) for filtering or tokei skill after refactoring to measure impact.

Key Options

Basic Output Control

• -f/--files show individual file statistics
• -l/--languages list supported languages and extensions
• -v/--verbose show unknown file extensions (1-3)
• -V/--version show version information
• --hidden include hidden files
• -c/--columns N set strict column width

Filtering & Exclusion

• -t/--type TYPES filter by language types (comma-separated)
• -e/--exclude PATTERNS exclude files/dirs (gitignore syntax)
• --no-ignore don't respect ignore files
  • --no-ignore-dot don't respect .ignore/.tokeignore
  • --no-ignore-vcs don't respect VCS ignore files
  • --no-ignore-parent don't respect parent ignore files

Output Formats

• -o/--output FORMAT output format (json|yaml|cbor)
  • Requires compilation with features: cargo install tokei --features all
• -i/--input FILE read from previous tokei run or stdin

Sorting Options

• -s/--sort COLUMN sort by column
  • Possible values: files|lines|blanks|code|comments

When to Use

• Project Analysis: Get comprehensive code statistics for entire codebase
• Language Breakdown: Understand project composition by language
• CI/CD Integration: Export metrics for build processes
• Code Auditing: Identify file types and their distributions
• Performance Monitoring: Track code growth over time

Core Principles

1. Speed: Optimized to count millions of lines in seconds
2. Accuracy: Correctly handles nested comments, multi-line strings
3. Language Coverage: Supports 150+ programming languages
4. Flexibility: Multiple output formats for integration

Detailed Reference

For comprehensive usage patterns, output formats, language filtering, and integration examples, load tokei guide when needing:

• Advanced language filtering and exclusion
• JSON/YAML output processing
• CI/CD integration patterns
• Docker usage examples
• Performance tuning for large codebases

The guide includes:

• Basic usage and output control options
• Language filtering and exclusion patterns
• Output format configuration (JSON, YAML, CBOR)
• Performance tips for large codebases
• Docker usage and CI/CD integration
• Configuration files and environment variables

Skill Combinations

For Discovery Phase

• fd → tokei: Analyze specific file types or directories
• extracting-code-structure → tokei: Get statistics for specific code components
• git diff → tokei: Analyze changed files statistics

For Analysis Phase

• tokei → jq/yq: Parse statistics output for reports
• tokei → fzf: Interactive selection from language breakdown
• tokei → bat: View statistics with formatted output

For Refactoring Phase

• tokei → replacing-text: Update configuration based on code statistics
• analyzing-code-structure → tokei: Measure impact of structural changes
• tokei → searching-text: Find files contributing to specific language statistics

Multi-Skill Workflows

• tokei → fd → searching-text → analyzing-code-structure: Statistics-driven refactoring pipeline
• tokei → jq → fzf: Interactive language-based file selection
• git workflow: git diff → tokei → fd → bat (analyze changes, select files, preview)

Integration Examples

# Get language breakdown and filter for top languages
tokei -o json | jq '.data | to_entries | sort_by(.value.stats.code) | reverse | .[0:5] | .[].key'

# Analyze changes after refactoring
git diff --name-only | xargs tokei --files

# Find and analyze specific components
fd -e py src/components | xargs tokei -t Python