| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.136 | | leniency | 0.273 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1534 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 67.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1534 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "eyebrow" | | 1 | "fractured" | | 2 | "pulsed" | | 3 | "trembled" | | 4 | "stomach" | | 5 | "flickered" | | 6 | "weight" | | 7 | "footsteps" |
| |
| 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 | 167 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 167 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 186 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1533 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 44.88% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 1427 | | uniqueNames | 6 | | maxNameDensity | 2.1 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 30 | | Morris | 1 | | Thames | 1 | | Rain | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | | globalScore | 0.449 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 109 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared beyond a stall of bottled shadows" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1533 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 186 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 111 | | mean | 13.81 | | std | 14.01 | | cv | 1.014 | | sampleLengths | | 0 | 12 | | 1 | 57 | | 2 | 2 | | 3 | 26 | | 4 | 4 | | 5 | 5 | | 6 | 39 | | 7 | 1 | | 8 | 2 | | 9 | 34 | | 10 | 3 | | 11 | 32 | | 12 | 36 | | 13 | 2 | | 14 | 25 | | 15 | 5 | | 16 | 49 | | 17 | 4 | | 18 | 1 | | 19 | 10 | | 20 | 7 | | 21 | 8 | | 22 | 8 | | 23 | 35 | | 24 | 5 | | 25 | 30 | | 26 | 36 | | 27 | 7 | | 28 | 2 | | 29 | 29 | | 30 | 6 | | 31 | 36 | | 32 | 4 | | 33 | 16 | | 34 | 3 | | 35 | 2 | | 36 | 12 | | 37 | 12 | | 38 | 2 | | 39 | 30 | | 40 | 6 | | 41 | 21 | | 42 | 1 | | 43 | 39 | | 44 | 8 | | 45 | 2 | | 46 | 20 | | 47 | 6 | | 48 | 4 | | 49 | 6 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 167 | | matches | | 0 | "been closed" | | 1 | "were jointed" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 256 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 186 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1433 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.018143754361479414 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0006978367062107466 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 186 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 186 | | mean | 8.24 | | std | 5.2 | | cv | 0.631 | | sampleLengths | | 0 | 12 | | 1 | 31 | | 2 | 9 | | 3 | 17 | | 4 | 2 | | 5 | 5 | | 6 | 8 | | 7 | 2 | | 8 | 11 | | 9 | 4 | | 10 | 5 | | 11 | 23 | | 12 | 9 | | 13 | 7 | | 14 | 1 | | 15 | 2 | | 16 | 13 | | 17 | 21 | | 18 | 3 | | 19 | 8 | | 20 | 17 | | 21 | 7 | | 22 | 22 | | 23 | 6 | | 24 | 8 | | 25 | 2 | | 26 | 8 | | 27 | 5 | | 28 | 12 | | 29 | 5 | | 30 | 7 | | 31 | 21 | | 32 | 8 | | 33 | 13 | | 34 | 4 | | 35 | 1 | | 36 | 5 | | 37 | 5 | | 38 | 7 | | 39 | 8 | | 40 | 8 | | 41 | 12 | | 42 | 8 | | 43 | 3 | | 44 | 12 | | 45 | 5 | | 46 | 15 | | 47 | 10 | | 48 | 5 | | 49 | 11 |
| |
| 49.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3172043010752688 | | totalSentences | 186 | | uniqueOpeners | 59 | |
| 42.74% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 156 | | matches | | 0 | "Then he slipped through the" | | 1 | "Somewhere, a creature whispered in" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 156 | | matches | | 0 | "Her boots struck the pavement" | | 1 | "She saw his face in" | | 2 | "He carried a leather satchel" | | 3 | "Its buckle flashed silver as" | | 4 | "She knew how panic shortened" | | 5 | "She crossed the street without" | | 6 | "Her shoulder scraped a drainpipe." | | 7 | "She caught it before it" | | 8 | "He planted one foot on" | | 9 | "He looked over his shoulder." | | 10 | "He gave her a thin" | | 11 | "Her leather watch snagged on" | | 12 | "She did not look back." | | 13 | "She pushed upright and sprinted." | | 14 | "Its iron gates stood chained," | | 15 | "He vanished below street level." | | 16 | "She drew her torch." | | 17 | "He was already forcing open" | | 18 | "It held calculation." | | 19 | "Her boots struck the tiles." |
| | ratio | 0.244 | |
| 11.28% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 140 | | totalSentences | 156 | | matches | | 0 | "Detective Harlow Quinn cut through" | | 1 | "Her boots struck the pavement" | | 2 | "The crowd broke in fragments." | | 3 | "A woman screamed when Quinn" | | 4 | "A taxi horn blared, then" | | 5 | "The suspect glanced back." | | 6 | "That was all Quinn needed." | | 7 | "She saw his face in" | | 8 | "He carried a leather satchel" | | 9 | "Its buckle flashed silver as" | | 10 | "Quinn had spent eighteen years" | | 11 | "She knew how panic shortened" | | 12 | "The satchel mattered." | | 13 | "She crossed the street without" | | 14 | "A double-decker bus roared past" | | 15 | "Quinn staggered, caught herself, and" | | 16 | "The man vaulted a waist-high" | | 17 | "Rain poured from fire escapes" | | 18 | "Neon fractured in the puddles" | | 19 | "The lane pinched tight between" |
| | ratio | 0.897 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 156 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 3 | | matches | | 0 | "Quinn had spent eighteen years chasing people who believed darkness made them invisible." | | 1 | "Some had faces that made Quinn’s stomach tighten: eyes too large, mouths split by narrow seams, skin patterned with scales or ash-grey veins." | | 2 | "Tables displayed bottles, knives, black candles, sealed envelopes and things that shifted under cloth." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.091 | | leniency | 0.182 | | rawRatio | 0 | | effectiveRatio | 0 | |