| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 89 | | tagDensity | 0.258 | | leniency | 0.517 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2137 | | 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) | |
| 81.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2137 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "etched" | | 1 | "weight" | | 2 | "trembled" | | 3 | "silk" | | 4 | "traced" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 190 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 190 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 256 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2137 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 14.13% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 98 | | wordCount | 1656 | | uniqueNames | 11 | | maxNameDensity | 2.72 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 45 | | British | 1 | | Museum | 1 | | Camden | 1 | | Nair | 16 | | Eva | 23 | | Morris | 3 | | Several | 1 | | One | 3 | | Three | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Nair" | | 3 | "Eva" | | 4 | "Morris" | | 5 | "One" |
| | places | (empty) | | globalScore | 0.141 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 120 | | 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 | 2137 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 256 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 130 | | mean | 16.44 | | std | 16.36 | | cv | 0.995 | | sampleLengths | | 0 | 4 | | 1 | 38 | | 2 | 10 | | 3 | 26 | | 4 | 13 | | 5 | 3 | | 6 | 5 | | 7 | 7 | | 8 | 16 | | 9 | 56 | | 10 | 44 | | 11 | 14 | | 12 | 4 | | 13 | 20 | | 14 | 3 | | 15 | 26 | | 16 | 62 | | 17 | 4 | | 18 | 10 | | 19 | 26 | | 20 | 6 | | 21 | 2 | | 22 | 3 | | 23 | 4 | | 24 | 7 | | 25 | 30 | | 26 | 4 | | 27 | 5 | | 28 | 8 | | 29 | 5 | | 30 | 7 | | 31 | 6 | | 32 | 4 | | 33 | 5 | | 34 | 31 | | 35 | 51 | | 36 | 27 | | 37 | 6 | | 38 | 5 | | 39 | 4 | | 40 | 4 | | 41 | 11 | | 42 | 1 | | 43 | 8 | | 44 | 9 | | 45 | 51 | | 46 | 15 | | 47 | 23 | | 48 | 4 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 190 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 283 | | matches | (empty) | |
| 98.21% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 4 | | flaggedSentences | 4 | | totalSentences | 256 | | ratio | 0.016 | | matches | | 0 | "One counter held stoppered bottles wrapped in black cloth; another displayed knives with paper tags tied round their handles." | | 1 | "Little blood on the front of the shirt; far more had soaked into the collar at the back." | | 2 | "No trains ran through the station; the tunnel lay dark beyond the platform lamps." | | 3 | "One held a tooth large enough to belong to a horse; another held a curl of human hair tied with green thread." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1657 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.013277006638503319 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0024140012070006035 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 256 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 256 | | mean | 8.35 | | std | 5.38 | | cv | 0.645 | | sampleLengths | | 0 | 4 | | 1 | 12 | | 2 | 26 | | 3 | 10 | | 4 | 11 | | 5 | 15 | | 6 | 4 | | 7 | 9 | | 8 | 3 | | 9 | 5 | | 10 | 7 | | 11 | 12 | | 12 | 4 | | 13 | 11 | | 14 | 4 | | 15 | 23 | | 16 | 6 | | 17 | 12 | | 18 | 10 | | 19 | 4 | | 20 | 19 | | 21 | 11 | | 22 | 14 | | 23 | 4 | | 24 | 20 | | 25 | 3 | | 26 | 14 | | 27 | 12 | | 28 | 6 | | 29 | 17 | | 30 | 6 | | 31 | 19 | | 32 | 4 | | 33 | 10 | | 34 | 4 | | 35 | 6 | | 36 | 4 | | 37 | 8 | | 38 | 18 | | 39 | 6 | | 40 | 2 | | 41 | 3 | | 42 | 4 | | 43 | 7 | | 44 | 11 | | 45 | 3 | | 46 | 16 | | 47 | 4 | | 48 | 5 | | 49 | 8 |
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| 50.26% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.30859375 | | totalSentences | 256 | | uniqueOpeners | 79 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 167 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 167 | | matches | | 0 | "It slid six inches towards" | | 1 | "Her worn leather watch knocked" | | 2 | "Their owners had fled." | | 3 | "Her worn leather satchel bulged" | | 4 | "He had the fixed stare" | | 5 | "She could press Eva later." | | 6 | "She could read a price" | | 7 | "Her grip tightened on the" | | 8 | "She said nothing." | | 9 | "She still remembered the smell" | | 10 | "It looked older than the" | | 11 | "She followed the needle towards" | | 12 | "Its point remained fixed on" | | 13 | "Its heel dropped over the" | | 14 | "She laid one end beside" | | 15 | "She dragged it back." | | 16 | "It glistened, sticky, then clung" | | 17 | "They formed a loose net," | | 18 | "They shifted the unit far" | | 19 | "She traced the tube to" |
| | ratio | 0.144 | |
| 37.84% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 141 | | totalSentences | 167 | | matches | | 0 | "Detective Harlow Quinn stopped on" | | 1 | "The woman beside the corpse" | | 2 | "The warning, though, came a" | | 3 | "It slid six inches towards" | | 4 | "A strip of white paper" | | 5 | "Quinn caught the handrail." | | 6 | "Her worn leather watch knocked" | | 7 | "the woman said" | | 8 | "The woman tucked a curl" | | 9 | "Quinn came down the last" | | 10 | "Crime scenes punished haste." | | 11 | "This one had drawn her" | | 12 | "Someone had painted over every" | | 13 | "Someone else had kept the" | | 14 | "Canvas stalls stood in two" | | 15 | "Their owners had fled." | | 16 | "Tea, hot wax and an" | | 17 | "A uniformed constable stood by" | | 18 | "Quinn asked him" | | 19 | "Nair glanced at the body" |
| | ratio | 0.844 | |
| 29.94% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 167 | | matches | | 0 | "If someone had cut his" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 74 | | technicalSentenceCount | 1 | | matches | | 0 | "He had the fixed stare of an officer who wanted somebody else to take his statement before he had to describe the body moving on its own." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 19 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 89 | | tagDensity | 0.213 | | leniency | 0.427 | | rawRatio | 0 | | effectiveRatio | 0 | |