Module: Ace::Bundle::Atoms::TypoDetector

Defined in:
lib/ace/bundle/atoms/typo_detector.rb

Overview

Pure functions for detecting typos in frontmatter keys Uses Levenshtein-like edit distance for similarity detection

Constant Summary collapse

KNOWN_FRONTMATTER_KEYS =

Known keys for templates and workflows

%w[
  context files commands include exclude diffs
  name description allowed-tools params argument-hint
  update frequency sections last-updated
  auto_generate template-refs embed_document_source
  doc-type purpose source title author version
].freeze

Class Method Summary collapse

Class Method Details

.detect_suspicious_keys(frontmatter, path) ⇒ Array<String>

Detect suspicious frontmatter keys that might be typos

Parameters:

  • frontmatter (Hash) —

    Parsed frontmatter YAML

  • path (String) —

    File path for warning message

Returns:

  • (Array<String>) —

    List of warning messages



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# File 'lib/ace/bundle/atoms/typo_detector.rb', line 23

def detect_suspicious_keys(frontmatter, path)
  warnings = []
  frontmatter.keys.each do |key|
    next if KNOWN_FRONTMATTER_KEYS.include?(key)

    # Check for common typos using Levenshtein-like distance
    KNOWN_FRONTMATTER_KEYS.each do |known|
      if typo_distance(key, known) <= 2
        warnings << "Possible typo in #{path}: frontmatter key '#{key}' looks similar to known key '#{known}'"
        break
      end
    end
  end

  warnings
end

.typo_distance(str1, str2) ⇒ Integer

Calculate simple edit distance between two strings Uses Levenshtein distance algorithm

Parameters:

  • str1 (String) —

    First string

  • str2 (String) —

    Second string

Returns:

  • (Integer) —

    Edit distance



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# File 'lib/ace/bundle/atoms/typo_detector.rb', line 45

def typo_distance(str1, str2)
  return str2.length if str1.empty?
  return str1.length if str2.empty?

  # Create distance matrix
  rows = str1.length + 1
  cols = str2.length + 1
  dist = Array.new(rows) { Array.new(cols, 0) }

  # Initialize first row and column
  (0...rows).each { |i| dist[i][0] = i }
  (0...cols).each { |j| dist[0][j] = j }

  # Fill in rest of matrix
  (1...rows).each do |i|
    (1...cols).each do |j|
      cost = (str1[i - 1] == str2[j - 1]) ? 0 : 1
      dist[i][j] = [
        dist[i - 1][j] + 1,     # deletion
        dist[i][j - 1] + 1,     # insertion
        dist[i - 1][j - 1] + cost # substitution
      ].min
    end
  end

  dist[rows - 1][cols - 1]
end