| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 2 | | adverbTags | | 0 | "She crouched again [again]" | | 1 | "Kowalski said finally [finally]" |
| | dialogueSentences | 44 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.182 | | effectiveRatio | 0.091 | |
| 85.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1667 | | totalAiIsmAdverbs | 5 | | found | | 0 | | | 1 | | | 2 | | adverb | "deliberately" | | count | 1 |
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| | highlights | | 0 | "slightly" | | 1 | "carefully" | | 2 | "deliberately" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 79.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1667 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "methodical" | | 1 | "etched" | | 2 | "standard" | | 3 | "calibrated" | | 4 | "measured" | | 5 | "pulse" | | 6 | "silence" |
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| 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 | 130 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 130 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 161 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1683 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 1232 | | uniqueNames | 10 | | maxNameDensity | 0.97 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 12 | | Tube | 1 | | Patel | 8 | | Underground | 1 | | Morris | 3 | | British | 2 | | Museum | 2 | | Kowalski | 2 | | Guarded | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Patel" | | 3 | "Morris" | | 4 | "Museum" | | 5 | "Kowalski" |
| | places | | | globalScore | 1 | | windowScore | 0.833 | |
| 80.56% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 2 | | matches | | 0 | "something like this before" | | 1 | "looked like a staff corridor" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1683 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 161 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 29.02 | | std | 25.45 | | cv | 0.877 | | sampleLengths | | 0 | 46 | | 1 | 76 | | 2 | 40 | | 3 | 2 | | 4 | 33 | | 5 | 10 | | 6 | 6 | | 7 | 65 | | 8 | 71 | | 9 | 64 | | 10 | 5 | | 11 | 15 | | 12 | 3 | | 13 | 33 | | 14 | 7 | | 15 | 3 | | 16 | 11 | | 17 | 3 | | 18 | 105 | | 19 | 36 | | 20 | 2 | | 21 | 20 | | 22 | 63 | | 23 | 48 | | 24 | 38 | | 25 | 6 | | 26 | 3 | | 27 | 18 | | 28 | 16 | | 29 | 50 | | 30 | 7 | | 31 | 79 | | 32 | 54 | | 33 | 6 | | 34 | 66 | | 35 | 12 | | 36 | 60 | | 37 | 2 | | 38 | 57 | | 39 | 24 | | 40 | 29 | | 41 | 39 | | 42 | 42 | | 43 | 6 | | 44 | 52 | | 45 | 21 | | 46 | 17 | | 47 | 21 | | 48 | 12 | | 49 | 8 |
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| 94.47% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 130 | | matches | | 0 | "been pulled" | | 1 | "was unbuttoned" | | 2 | "been closed" | | 3 | "was etched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 214 | | matches | | 0 | "was looking" | | 1 | "was waiting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 0 | | flaggedSentences | 13 | | totalSentences | 161 | | ratio | 0.081 | | matches | | 0 | "Not blood — she knew blood, could pick it from a catalogue of a hundred crime-scene scents without pausing." | | 1 | "The overhead lights — rigged by forensics, temporary and harsh — threw everything into flat, clinical relief." | | 2 | "Eighteen years on the force had taught her to read a crime scene the way some people read newspapers — start with the headline, then work down to the fine print." | | 3 | "They stared at the vaulted ceiling with an expression Quinn had seen before — not fear, not pain." | | 4 | "His shirt was unbuttoned, pulled open to reveal a chest that was — wrong." | | 5 | "But this one — she'd pulled the file on the drive over — had a history." | | 6 | "The face was etched with symbols she didn't recognise — not standard navigation markings, not any alphabet she'd seen." | | 7 | "She measured the distance between them with her hands — roughly a metre apart, forming a square." | | 8 | "The chalk marks were faint, but under the forensic light, she could see something else — a shimmer, almost imperceptible, like heat haze." | | 9 | "She looked at the body one more time — the surprised eyes, the translucent skin, the careful arrangement." | | 10 | "It kept time the way he'd kept time — precise, reliable, slightly fast." | | 11 | "The smile in the photograph was academic — polite, slightly distracted." | | 12 | "Quinn could almost hear the calculations happening on the other end — the weighing of risk, the measuring of trust." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1221 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.027846027846027847 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.006552006552006552 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 161 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 161 | | mean | 10.45 | | std | 8.53 | | cv | 0.816 | | sampleLengths | | 0 | 5 | | 1 | 19 | | 2 | 4 | | 3 | 2 | | 4 | 16 | | 5 | 19 | | 6 | 13 | | 7 | 17 | | 8 | 6 | | 9 | 21 | | 10 | 18 | | 11 | 16 | | 12 | 6 | | 13 | 2 | | 14 | 5 | | 15 | 28 | | 16 | 10 | | 17 | 3 | | 18 | 3 | | 19 | 4 | | 20 | 30 | | 21 | 31 | | 22 | 10 | | 23 | 2 | | 24 | 2 | | 25 | 1 | | 26 | 12 | | 27 | 4 | | 28 | 18 | | 29 | 1 | | 30 | 21 | | 31 | 4 | | 32 | 6 | | 33 | 14 | | 34 | 2 | | 35 | 2 | | 36 | 16 | | 37 | 20 | | 38 | 5 | | 39 | 15 | | 40 | 3 | | 41 | 12 | | 42 | 21 | | 43 | 3 | | 44 | 4 | | 45 | 3 | | 46 | 11 | | 47 | 3 | | 48 | 7 | | 49 | 13 |
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| 64.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.42857142857142855 | | totalSentences | 161 | | uniqueOpeners | 69 | |
| 32.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 103 | | matches | | 0 | "Then the soft sound of" |
| | ratio | 0.01 | |
| 72.43% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 103 | | matches | | 0 | "Her shoes scraped against tile" | | 1 | "He was young, methodical, the" | | 2 | "Her worn leather watch caught" | | 3 | "His eyes were open." | | 4 | "They stared at the vaulted" | | 5 | "She crouched beside him." | | 6 | "His shirt was unbuttoned, pulled" | | 7 | "She could see the shadow" | | 8 | "She stood, her knees protesting" | | 9 | "She filed that away and" | | 10 | "She turned it over." | | 11 | "He led her to the" | | 12 | "She measured the distance between" | | 13 | "She looked back at the" | | 14 | "She walked to the compass" | | 15 | "She looked at Patel" | | 16 | "She crouched again, this time" | | 17 | "She leaned closer." | | 18 | "Her jaw tightened." | | 19 | "She had seen something like" |
| | ratio | 0.369 | |
| 37.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 87 | | totalSentences | 103 | | matches | | 0 | "The smell hit her first." | | 1 | "This was something else." | | 2 | "Detective Harlow Quinn ducked beneath" | | 3 | "Her shoes scraped against tile" | | 4 | "The overhead lights — rigged" | | 5 | "Archways gaped dark on either" | | 6 | "The tracks had been pulled" | | 7 | "DS Patel straightened from where" | | 8 | "He was young, methodical, the" | | 9 | "Patel gestured toward the body." | | 10 | "Patel's mouth thinned." | | 11 | "Quinn crossed the platform." | | 12 | "Her worn leather watch caught" | | 13 | "The body lay in a" | | 14 | "The man's arms were at" | | 15 | "His eyes were open." | | 16 | "They stared at the vaulted" | | 17 | "The kind of look that" | | 18 | "She crouched beside him." | | 19 | "The copper smell was stronger" |
| | ratio | 0.845 | |
| 48.54% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 103 | | matches | | | ratio | 0.01 | |
| 50.26% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 7 | | matches | | 0 | "Like wet stone and copper and the particular staleness of air that hadn't moved in decades." | | 1 | "The tracks had been pulled up long ago, leaving shallow trenches filled with stagnant water that caught the light like oil." | | 2 | "He was young, methodical, the kind of officer who wrote reports that read like instruction manuals." | | 3 | "She could see the shadow of ribs beneath, the faint suggestion of architecture that shouldn't be visible from the outside." | | 4 | "Urban explorers who came back disoriented, claiming they'd found passages that weren't on any map." | | 5 | "The metallic component in the chalk caught the light and threw it back in a colour that wasn't quite gold and wasn't quite green." | | 6 | "Below ground, the forensic team would still be working, cataloguing evidence that wouldn't fit into any report she'd ever filed." |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "Patel stepped, his notebook open" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 44 | | tagDensity | 0.114 | | leniency | 0.227 | | rawRatio | 0 | | effectiveRatio | 0 | |