| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn knelt again [again]" |
| | dialogueSentences | 79 | | tagDensity | 0.139 | | leniency | 0.278 | | rawRatio | 0.091 | | effectiveRatio | 0.025 | |
| 94.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2894 | | totalAiIsmAdverbs | 3 | | found | | 0 | | adverb | "deliberately" | | count | 1 |
| | 1 | | | 2 | |
| | highlights | | 0 | "deliberately" | | 1 | "completely" | | 2 | "carefully" |
| |
| 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) | |
| 48.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2894 | | totalAiIsms | 30 | | found | | | highlights | | 0 | "shattered" | | 1 | "perfect" | | 2 | "stark" | | 3 | "scanned" | | 4 | "pumping" | | 5 | "standard" | | 6 | "weight" | | 7 | "trembled" | | 8 | "magnetic" | | 9 | "flickered" | | 10 | "etched" | | 11 | "traced" | | 12 | "fractured" | | 13 | "pulsed" | | 14 | "echoing" | | 15 | "footsteps" | | 16 | "echoed" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 174 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 174 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 242 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 72 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2894 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 83 | | wordCount | 1112 | | uniqueNames | 10 | | maxNameDensity | 3.15 | | worstName | "Quinn" | | maxWindowNameDensity | 6 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Met | 1 | | Quinn | 35 | | Kowalski | 1 | | Eva | 32 | | Veil | 2 | | Compass | 2 | | Rotherhithe | 1 | | Rain | 5 | | Fluorescent | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Kowalski" | | 2 | "Eva" | | 3 | "Compass" | | 4 | "Rain" | | 5 | "Fluorescent" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 96 | | 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 | 2894 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 242 | | matches | (empty) | |
| 80.86% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 75 | | mean | 38.59 | | std | 16.71 | | cv | 0.433 | | sampleLengths | | 0 | 104 | | 1 | 35 | | 2 | 54 | | 3 | 16 | | 4 | 61 | | 5 | 9 | | 6 | 35 | | 7 | 37 | | 8 | 44 | | 9 | 34 | | 10 | 46 | | 11 | 16 | | 12 | 67 | | 13 | 69 | | 14 | 32 | | 15 | 49 | | 16 | 56 | | 17 | 18 | | 18 | 24 | | 19 | 12 | | 20 | 72 | | 21 | 43 | | 22 | 61 | | 23 | 65 | | 24 | 42 | | 25 | 80 | | 26 | 27 | | 27 | 67 | | 28 | 25 | | 29 | 71 | | 30 | 19 | | 31 | 56 | | 32 | 35 | | 33 | 46 | | 34 | 42 | | 35 | 37 | | 36 | 35 | | 37 | 27 | | 38 | 23 | | 39 | 28 | | 40 | 37 | | 41 | 33 | | 42 | 28 | | 43 | 21 | | 44 | 35 | | 45 | 31 | | 46 | 32 | | 47 | 29 | | 48 | 31 | | 49 | 35 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 174 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 218 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 242 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1115 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.015246636771300448 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003587443946188341 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 242 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 242 | | mean | 11.96 | | std | 11.09 | | cv | 0.928 | | sampleLengths | | 0 | 10 | | 1 | 15 | | 2 | 10 | | 3 | 15 | | 4 | 14 | | 5 | 13 | | 6 | 5 | | 7 | 12 | | 8 | 10 | | 9 | 8 | | 10 | 27 | | 11 | 4 | | 12 | 15 | | 13 | 14 | | 14 | 5 | | 15 | 1 | | 16 | 1 | | 17 | 2 | | 18 | 8 | | 19 | 4 | | 20 | 16 | | 21 | 4 | | 22 | 9 | | 23 | 13 | | 24 | 5 | | 25 | 2 | | 26 | 8 | | 27 | 11 | | 28 | 9 | | 29 | 9 | | 30 | 35 | | 31 | 8 | | 32 | 7 | | 33 | 5 | | 34 | 6 | | 35 | 11 | | 36 | 16 | | 37 | 28 | | 38 | 2 | | 39 | 2 | | 40 | 13 | | 41 | 1 | | 42 | 16 | | 43 | 19 | | 44 | 27 | | 45 | 16 | | 46 | 6 | | 47 | 61 | | 48 | 3 | | 49 | 7 |
| |
| 51.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.325 | | totalSentences | 240 | | uniqueOpeners | 78 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 158 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 158 | | matches | | 0 | "She stepped over the caution" | | 1 | "She crouched beside the body," | | 2 | "She scanned the perimeter." | | 3 | "She tucked a curl of" | | 4 | "She turned her wrist, checking" | | 5 | "She brushed a glove over" | | 6 | "She rubbed it between thumb" | | 7 | "She looked at the fused" | | 8 | "She reached into her trench" | | 9 | "She flipped the glass cover" | | 10 | "It pointed straight at the" | | 11 | "She lowered the penlight." | | 12 | "She looked at the spray" | | 13 | "They laid out operational grids." | | 14 | "She swept her gloved hand" | | 15 | "She slipped it back into" | | 16 | "She stared at the fused" | | 17 | "She carefully extracted the inner" | | 18 | "She pulled her coat tight." | | 19 | "She opened a notes application." |
| | ratio | 0.133 | |
| 10.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 142 | | totalSentences | 158 | | matches | | 0 | "Rain slicked the rusted grating" | | 1 | "Quinn stepped past the yellow" | | 2 | "The Met cordon stretched tight," | | 3 | "Flashlights cut through the damp" | | 4 | "The victim sat upright against" | | 5 | "The damp concrete remained dry" | | 6 | "A stark contrast to the" | | 7 | "A uniformed sergeant straightened his" | | 8 | "Quinn nodded, jaw tightening." | | 9 | "She stepped over the caution" | | 10 | "The smell hit her first." | | 11 | "She crouched beside the body," | | 12 | "She scanned the perimeter." | | 13 | "Spray paint covered the walls" | | 14 | "Someone used a blowtorch to" | | 15 | "A maintenance lift couldn't reach" | | 16 | "The city hadn't authorised heavy" | | 17 | "A worn leather satchel thumped" | | 18 | "Eva Kowalski stepped into the" | | 19 | "Freckles stood out across her" |
| | ratio | 0.899 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 158 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |