| 46.15% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "Davies frowned clearly [clearly]" | | 1 | "She knelt again [again]" |
| | dialogueSentences | 24 | | tagDensity | 0.542 | | leniency | 1 | | rawRatio | 0.154 | | effectiveRatio | 0.154 | |
| 81.63% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1089 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | |
| | highlights | | 0 | "slowly" | | 1 | "deliberately" | | 2 | "suddenly" |
| |
| 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) | |
| 17.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1089 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "chill" | | 1 | "pulsed" | | 2 | "rhythmic" | | 3 | "mechanical" | | 4 | "echoed" | | 5 | "chaotic" | | 6 | "echoing" | | 7 | "remarkable" | | 8 | "intricate" | | 9 | "etched" | | 10 | "oppressive" | | 11 | "flicker" | | 12 | "familiar" | | 13 | "scanned" | | 14 | "whisper" | | 15 | "echo" | | 16 | "resonance" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 103 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 103 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 10 | | totalWords | 1089 | | ratio | 0.009 | | matches | | 0 | "away" | | 1 | "into" | | 2 | "He sought knowledge... and knowledge demands a price." |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 868 | | uniqueNames | 14 | | maxNameDensity | 0.92 | | worstName | "Davies" | | maxWindowNameDensity | 2 | | worstWindowName | "Davies" | | discoveredNames | | Quinn | 1 | | Tube | 1 | | Veil | 4 | | Market | 3 | | Davies | 8 | | Bloomsbury | 1 | | Camden | 1 | | Harlow | 7 | | Finch | 4 | | Compass | 2 | | London | 1 | | Morris | 2 | | Suddenly | 1 | | Arthur | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Market" | | 2 | "Davies" | | 3 | "Harlow" | | 4 | "Finch" | | 5 | "Compass" | | 6 | "Morris" | | 7 | "Arthur" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 27.05% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 3 | | matches | | 0 | "quite place—a mechanical thrum overlaid with something older, something deeper" | | 1 | "looked like a hurried meal scattered near" | | 2 | "A whisper, seemingly from everywhere and" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1089 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 114 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 32.03 | | std | 20 | | cv | 0.625 | | sampleLengths | | 0 | 80 | | 1 | 59 | | 2 | 25 | | 3 | 27 | | 4 | 67 | | 5 | 24 | | 6 | 9 | | 7 | 32 | | 8 | 61 | | 9 | 14 | | 10 | 19 | | 11 | 56 | | 12 | 21 | | 13 | 42 | | 14 | 15 | | 15 | 15 | | 16 | 40 | | 17 | 8 | | 18 | 7 | | 19 | 57 | | 20 | 17 | | 21 | 43 | | 22 | 34 | | 23 | 28 | | 24 | 28 | | 25 | 36 | | 26 | 27 | | 27 | 9 | | 28 | 14 | | 29 | 34 | | 30 | 17 | | 31 | 8 | | 32 | 40 | | 33 | 76 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 103 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 138 | | matches | | |
| 92.73% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 114 | | ratio | 0.018 | | matches | | 0 | "The abandoned Tube station pulsed with a low, rhythmic hum she couldn’t quite place—a mechanical thrum overlaid with something older, something deeper." | | 1 | "The usual chaotic energy of the Market – the frantic bartering, the whispers of forbidden secrets – was absent, replaced by this unsettling quiet." |
| |
| 78.22% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 868 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 50 | | adverbRatio | 0.0576036866359447 | | lyAdverbCount | 24 | | lyAdverbRatio | 0.027649769585253458 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 9.55 | | std | 7.23 | | cv | 0.757 | | sampleLengths | | 0 | 13 | | 1 | 17 | | 2 | 22 | | 3 | 3 | | 4 | 15 | | 5 | 10 | | 6 | 33 | | 7 | 19 | | 8 | 4 | | 9 | 1 | | 10 | 2 | | 11 | 9 | | 12 | 7 | | 13 | 9 | | 14 | 6 | | 15 | 4 | | 16 | 1 | | 17 | 11 | | 18 | 2 | | 19 | 3 | | 20 | 5 | | 21 | 9 | | 22 | 17 | | 23 | 2 | | 24 | 1 | | 25 | 4 | | 26 | 5 | | 27 | 24 | | 28 | 9 | | 29 | 8 | | 30 | 4 | | 31 | 2 | | 32 | 1 | | 33 | 9 | | 34 | 20 | | 35 | 12 | | 36 | 9 | | 37 | 12 | | 38 | 2 | | 39 | 5 | | 40 | 11 | | 41 | 5 | | 42 | 17 | | 43 | 14 | | 44 | 19 | | 45 | 4 | | 46 | 8 | | 47 | 5 | | 48 | 16 | | 49 | 13 |
| |
| 62.57% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.41228070175438597 | | totalSentences | 114 | | uniqueOpeners | 47 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 86 | | matches | | 0 | "Officially, it was just another" | | 1 | "Unofficially, it was a headache" | | 2 | "Then she noticed it." | | 3 | "Suddenly, the hum intensified, vibrating" |
| | ratio | 0.047 | |
| 94.42% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 86 | | matches | | 0 | "His voice echoed in the" | | 1 | "It was supposed to be" | | 2 | "She ran a gloved hand" | | 3 | "she asked, her voice echoing" | | 4 | "He clutched a small object," | | 5 | "she asked, deliberately keeping her" | | 6 | "It shouldn't be doing that." | | 7 | "It was a tool for" | | 8 | "She glanced around the station." | | 9 | "She rose, her gaze sweeping" | | 10 | "she stated, her voice low" | | 11 | "She knelt again, examining the" | | 12 | "she said, slowly" | | 13 | "She pointed to the crumbs" | | 14 | "She remembered a case three" | | 15 | "She focused again on Finch’s" | | 16 | "she murmured, mostly to herself" | | 17 | "she ordered Davies" | | 18 | "He looked at her, his" | | 19 | "Her gaze drifted to the" |
| | ratio | 0.314 | |
| 70.47% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 86 | | matches | | 0 | "The air hung thick and" | | 1 | "Harlow Quinn adjusted the collar" | | 2 | "The abandoned Tube station pulsed" | | 3 | "The Veil Market." | | 4 | "The body lay slumped against" | | 5 | "Sergeant Davies said, already on" | | 6 | "His voice echoed in the" | | 7 | "Harlow knelt, circling the body" | | 8 | "Davies was good, solid." | | 9 | "this wasn’t clean." | | 10 | "The station itself was wrong." | | 11 | "The Veil Market shifted, migrated" | | 12 | "It was supposed to be" | | 13 | "The usual chaotic energy of" | | 14 | "She ran a gloved hand" | | 15 | "The victim hadn’t fought." | | 16 | "she asked, her voice echoing" | | 17 | "Davies pointed to a small," | | 18 | "Harlow ignored him, her attention" | | 19 | "He clutched a small object," |
| | ratio | 0.779 | |
| 58.14% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 86 | | matches | | 0 | "Because whatever had killed Arthur" |
| | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 1 | | matches | | 0 | "Or rather, she sensed its echo, a faint resonance of the same presence she’d encountered three years ago, the same presence that had stolen DS Morris from her." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 5 | | matches | | 0 | "she asked, her voice echoing strangely" | | 1 | "she stated, her voice low" | | 2 | "she said, slowly" | | 3 | "she murmured, mostly to herself" | | 4 | "she muttered, her voice barely audible above the increasing hum" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 4 | | fancyTags | | 0 | "she stated (state)" | | 1 | "she murmured (murmur)" | | 2 | "she ordered (order)" | | 3 | "she muttered (mutter)" |
| | dialogueSentences | 24 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.5 | | effectiveRatio | 0.333 | |