| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 1 | | adverbTags | | 0 | "Lucien's voice cracked ever [ever]" |
| | dialogueSentences | 30 | | tagDensity | 0.733 | | leniency | 1 | | rawRatio | 0.045 | | effectiveRatio | 0.045 | |
| 64.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 711 | | totalAiIsmAdverbs | 5 | | found | | 0 | | adverb | "ever so slightly" | | count | 1 |
| | 1 | | | 2 | | adverb | "barely above a whisper" | | count | 1 |
| | 3 | | | 4 | |
| | highlights | | 0 | "ever so slightly" | | 1 | "softly" | | 2 | "barely above a whisper" | | 3 | "slowly" | | 4 | "truly" |
| |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 8.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 711 | | totalAiIsms | 13 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | word | "moth to a flame" | | count | 1 |
| | 10 | | | 11 | |
| | highlights | | 0 | "tension" | | 1 | "echoed" | | 2 | "whisper" | | 3 | "silence" | | 4 | "weight" | | 5 | "scanning" | | 6 | "resolve" | | 7 | "wavering" | | 8 | "warmth" | | 9 | "moth to a flame" | | 10 | "searing" | | 11 | "solace" |
| |
| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "heart pounded in chest" | | count | 2 |
| | 1 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | 0 | "heart pounded in her chest" | | 1 | "heart hammered in her chest" | | 2 | "eyes narrowed" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 37 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 37 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 45 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 710 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 56.19% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 533 | | uniqueNames | 5 | | maxNameDensity | 1.88 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Ptolemy | 1 | | Aurora | 10 | | Lucien | 7 | | Cardiff | 1 | | London | 1 |
| | persons | | | places | | | globalScore | 0.562 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 36 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 710 | | matches | (empty) | |
| 18.52% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 45 | | matches | | 0 | "insist that he leave, that they" |
| |
| 78.38% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 26.3 | | std | 11.16 | | cv | 0.424 | | sampleLengths | | 0 | 38 | | 1 | 34 | | 2 | 28 | | 3 | 36 | | 4 | 35 | | 5 | 44 | | 6 | 25 | | 7 | 21 | | 8 | 16 | | 9 | 21 | | 10 | 27 | | 11 | 26 | | 12 | 42 | | 13 | 42 | | 14 | 6 | | 15 | 43 | | 16 | 13 | | 17 | 22 | | 18 | 20 | | 19 | 17 | | 20 | 35 | | 21 | 16 | | 22 | 9 | | 23 | 15 | | 24 | 35 | | 25 | 10 | | 26 | 34 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 37 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 93 | | matches | (empty) | |
| 15.87% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 45 | | ratio | 0.044 | | matches | | 0 | "Aurora wanted to argue, to insist that he leave, that they could never work - but the words wouldn't come." | | 1 | "And there, in the cramped flat above the curry house, they came together - two lost souls finding solace in the chaos, two hearts that had never truly forgotten the rhythm of the other's beat." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 534 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 17 | | adverbRatio | 0.031835205992509365 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.013108614232209739 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 45 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 45 | | mean | 15.78 | | std | 7.96 | | cv | 0.504 | | sampleLengths | | 0 | 18 | | 1 | 20 | | 2 | 16 | | 3 | 18 | | 4 | 28 | | 5 | 36 | | 6 | 24 | | 7 | 11 | | 8 | 16 | | 9 | 10 | | 10 | 18 | | 11 | 25 | | 12 | 21 | | 13 | 7 | | 14 | 9 | | 15 | 9 | | 16 | 12 | | 17 | 19 | | 18 | 8 | | 19 | 13 | | 20 | 13 | | 21 | 22 | | 22 | 20 | | 23 | 20 | | 24 | 22 | | 25 | 6 | | 26 | 19 | | 27 | 24 | | 28 | 11 | | 29 | 2 | | 30 | 18 | | 31 | 4 | | 32 | 20 | | 33 | 9 | | 34 | 8 | | 35 | 20 | | 36 | 15 | | 37 | 9 | | 38 | 7 | | 39 | 9 | | 40 | 15 | | 41 | 35 | | 42 | 10 | | 43 | 31 | | 44 | 3 |
| |
| 71.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.5111111111111111 | | totalSentences | 45 | | uniqueOpeners | 23 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 37 | | matches | | 0 | "Slowly, Aurora stepped aside, allowing" | | 1 | "Instead, she found herself leaning" |
| | ratio | 0.054 | |
| 57.84% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 37 | | matches | | 0 | "He averted his gaze, a" | | 1 | "Her voice was steady, but" | | 2 | "he admitted, his voice barely" | | 3 | "His hand unconsciously tapped the" | | 4 | "He moved with a quiet" | | 5 | "he noted with a hint" | | 6 | "He moved towards her, closing" | | 7 | "she breathed, but there was" | | 8 | "he whispered, his fingers brushing" | | 9 | "she breathed, a soft surrender" | | 10 | "His arms wrapped around her," | | 11 | "he murmured against her lips," | | 12 | "she admitted, her hands fisting" | | 13 | "They tumbled onto it, lost" | | 14 | "he promised, his body covering" |
| | ratio | 0.405 | |
| 27.57% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 32 | | totalSentences | 37 | | matches | | 0 | "Lucien's voice cracked ever so" | | 1 | "Ptolemy, the tabby cat, meowed" | | 2 | "Aurora's bright blue eyes narrowed," | | 3 | "The scent of curry wafted" | | 4 | "He averted his gaze, a" | | 5 | "Her voice was steady, but" | | 6 | "he admitted, his voice barely" | | 7 | "His hand unconsciously tapped the" | | 8 | "He moved with a quiet" | | 9 | "he noted with a hint" | | 10 | "Aurora replied, crossing her arms" | | 11 | "Lucien began, his voice trailing" | | 12 | "He moved towards her, closing" | | 13 | "Aurora's heart hammered in her" | | 14 | "she breathed, but there was" | | 15 | "he whispered, his fingers brushing" | | 16 | "Aurora replied, her voice barely" | | 17 | "Lucien insisted, his hand cupping" | | 18 | "Aurora wanted to argue, to" | | 19 | "she breathed, a soft surrender" |
| | ratio | 0.865 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 37 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 13 | | technicalSentenceCount | 3 | | matches | | 0 | "His arms wrapped around her, pulling her close, and she found herself falling, tumbling head over heels into the fire that burned between them." | | 1 | "Lucien's response was swift, his arms lifting her, carrying her to the small bed in the corner of the flat." | | 2 | "And there, in the cramped flat above the curry house, they came together - two lost souls finding solace in the chaos, two hearts that had never truly forgotten…" |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 7 | | matches | | 0 | "blue eyes narrowed, her hand gripping the doorframe" | | 1 | "he admitted, his voice barely above a whisper" | | 2 | "Lucien began, his voice trailing off" | | 3 | "Aurora replied, her voice barely audible" | | 4 | "he murmured, his voice thick with emotion" | | 5 | "she admitted, her hands fisting in the material of his suit jacket" | | 6 | "Lucien whispered, his voice a vow" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 13 | | fancyTags | | 0 | "he admitted (admit)" | | 1 | "he noted (note)" | | 2 | "she breathed (breathe)" | | 3 | "he whispered (whisper)" | | 4 | "Lucien insisted (insist)" | | 5 | "she breathed (breathe)" | | 6 | "he murmured (murmur)" | | 7 | "she admitted (admit)" | | 8 | "Lucien urged (urge)" | | 9 | "Aurora admitted (admit)" | | 10 | "he promised (promise)" | | 11 | "Aurora breathed (breathe)" | | 12 | "Lucien whispered (whisper)" |
| | dialogueSentences | 30 | | tagDensity | 0.533 | | leniency | 1 | | rawRatio | 0.813 | | effectiveRatio | 0.813 | |