| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1206 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 62.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1206 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "shattered" | | 1 | "flicked" | | 2 | "jaw clenched" | | 3 | "measured" | | 4 | "lurched" | | 5 | "pulse" | | 6 | "pulsed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "clenched fist" | | 1 | "jaw clenched" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 116 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 116 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 121 | | 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 | 1202 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 94.54% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 1172 | | uniqueNames | 26 | | maxNameDensity | 1.11 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 13 | | Frith | 1 | | Street | 4 | | Raven | 1 | | Nest | 2 | | Herrera | 9 | | Saint | 1 | | Christopher | 1 | | Dean | 1 | | Greek | 1 | | St | 1 | | Court | 1 | | Constantine | 1 | | Camden | 3 | | Road | 1 | | High | 1 | | Tudor | 1 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Morris | 1 | | Mobiles | 1 | | Rain | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Market" | | 6 | "Morris" | | 7 | "Mobiles" | | 8 | "Rain" |
| | places | | 0 | "Soho" | | 1 | "Frith" | | 2 | "Street" | | 3 | "Raven" | | 4 | "Dean" | | 5 | "Greek" | | 6 | "St" | | 7 | "Constantine" | | 8 | "Camden" | | 9 | "Road" | | 10 | "High" |
| | globalScore | 0.945 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 91 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like human skin" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1202 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 121 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 54.64 | | std | 37.26 | | cv | 0.682 | | sampleLengths | | 0 | 64 | | 1 | 6 | | 2 | 62 | | 3 | 48 | | 4 | 3 | | 5 | 85 | | 6 | 88 | | 7 | 21 | | 8 | 4 | | 9 | 59 | | 10 | 67 | | 11 | 75 | | 12 | 8 | | 13 | 9 | | 14 | 9 | | 15 | 89 | | 16 | 25 | | 17 | 78 | | 18 | 126 | | 19 | 113 | | 20 | 74 | | 21 | 89 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 196 | | matches | (empty) | |
| 24.79% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 121 | | ratio | 0.041 | | matches | | 0 | "She felt the old exactness of footwork return—drive from the hip, lengthen the gait, keep the centre of mass low." | | 1 | "Herrera pressed something white and dry against the padlock—an irregular disc the size of a coin, hollow at the centre, the unmistakable curl of bone." | | 2 | "Cloth canopies hid what hung for sale—jars of pale liquid swirling without being stirred, bundles of feathers stitched with copper wire, drawers of teeth that still held their root." | | 3 | "She remembered the unexplained detonation that took DS Morris three years earlier—the way the soft tissues of his face blackened at the edges while the walls around him remained whole." | | 4 | "Radio reception died two metres past the boarded door; she already knew that from the dead crackle on her handset." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1183 | | adjectiveStacks | 1 | | stackExamples | | 0 | "ahead, curly dark hair" |
| | adverbCount | 25 | | adverbRatio | 0.021132713440405747 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.00422654268808115 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 121 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 121 | | mean | 9.93 | | std | 5.86 | | cv | 0.59 | | sampleLengths | | 0 | 15 | | 1 | 5 | | 2 | 13 | | 3 | 23 | | 4 | 8 | | 5 | 6 | | 6 | 7 | | 7 | 12 | | 8 | 4 | | 9 | 10 | | 10 | 17 | | 11 | 3 | | 12 | 9 | | 13 | 5 | | 14 | 4 | | 15 | 8 | | 16 | 6 | | 17 | 7 | | 18 | 6 | | 19 | 6 | | 20 | 6 | | 21 | 3 | | 22 | 13 | | 23 | 6 | | 24 | 11 | | 25 | 2 | | 26 | 22 | | 27 | 8 | | 28 | 3 | | 29 | 6 | | 30 | 6 | | 31 | 8 | | 32 | 12 | | 33 | 5 | | 34 | 8 | | 35 | 13 | | 36 | 8 | | 37 | 19 | | 38 | 11 | | 39 | 5 | | 40 | 7 | | 41 | 11 | | 42 | 3 | | 43 | 7 | | 44 | 4 | | 45 | 4 | | 46 | 10 | | 47 | 3 | | 48 | 7 | | 49 | 2 |
| |
| 74.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.45454545454545453 | | totalSentences | 121 | | uniqueOpeners | 55 | |
| 29.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 113 | | matches | | 0 | "Somewhere deeper a generator coughed" |
| | ratio | 0.009 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 113 | | matches | | 0 | "He cut left into Dean" | | 1 | "Her closely cropped salt-and-pepper hair" | | 2 | "She shouldered through them without" | | 3 | "He ignored the shouted order" | | 4 | "Her brown eyes locked on" | | 5 | "She took the gate in" | | 6 | "Her lungs drew cold air" | | 7 | "He veered into a pedestrian" | | 8 | "She mirrored each move, left" | | 9 | "She trapped the doors with" | | 10 | "He dropped into the road" | | 11 | "She fixed her gaze on" | | 12 | "He spent the next hundred" | | 13 | "He crossed against the lights." | | 14 | "Her watch ticked another cold" | | 15 | "She felt the old exactness" | | 16 | "His reply came ragged between" | | 17 | "He swerved into the mouth" | | 18 | "He slipped through the warped" | | 19 | "Her chest rose and fell" |
| | ratio | 0.212 | |
| 44.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 94 | | totalSentences | 113 | | matches | | 0 | "Rain lashed the Soho pavement" | | 1 | "Puddles shattered under her boots." | | 2 | "Tomás Herrera burst through the" | | 3 | "The Saint Christopher medallion bounced" | | 4 | "Herrera's warm brown eyes flicked" | | 5 | "He cut left into Dean" | | 6 | "Quinn matched his pace." | | 7 | "Her closely cropped salt-and-pepper hair" | | 8 | "The worn leather watch on" | | 9 | "Military precision held her stride" | | 10 | "A black cab horn blared." | | 11 | "Herrera vaulted its bonnet." | | 12 | "Quinn cleared the same vehicle" | | 13 | "Crowds spilled from a late" | | 14 | "She shouldered through them without" | | 15 | "A woman in heels staggered" | | 16 | "A glass shattered on the" | | 17 | "He ignored the shouted order" | | 18 | "Bin bags sagged against brick" | | 19 | "The stink of sour beer" |
| | ratio | 0.832 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 113 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 3 | | matches | | 0 | "The air rising from below carried iron, candle wax, and a sharp chemical bite that stuck in the sinuses." | | 1 | "She remembered the unexplained detonation that took DS Morris three years earlier—the way the soft tissues of his face blackened at the edges while the walls ar…" | | 2 | "Superiors who closed ranks and told her the case was coincidence and fire." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |