| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn moved back [back]" | | 1 | "the evidence bag pulled slightly [slightly]" |
| | dialogueSentences | 48 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0.133 | | effectiveRatio | 0.083 | |
| 87.12% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1165 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "completely" | | 2 | "slightly" |
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| 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) | |
| 44.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1165 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "perfect" | | 1 | "etched" | | 2 | "magnetic" | | 3 | "depths" | | 4 | "familiar" | | 5 | "database" | | 6 | "footsteps" | | 7 | "echoed" | | 8 | "silence" |
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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 | 90 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 90 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 123 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 24 | | totalWords | 1162 | | ratio | 0.021 | | matches | | 0 | "Found something interesting in the archives. Call me." | | 1 | "Seriously, Harlow. This is important. Those symbols you asked about last month? I found a match." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 44.18% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 756 | | uniqueNames | 16 | | maxNameDensity | 2.12 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 2 | | Camden | 1 | | Briggs | 6 | | Detective | 1 | | Harlow | 2 | | Quinn | 16 | | Underground | 1 | | Morris | 5 | | Kowalski | 1 | | Met | 1 | | Last | 1 | | Shoreditch | 1 | | Papers | 1 | | Eva | 4 | | Footsteps | 1 | | Silence | 1 |
| | persons | | 0 | "Briggs" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Kowalski" | | 5 | "Papers" | | 6 | "Eva" | | 7 | "Footsteps" | | 8 | "Silence" |
| | places | (empty) | | globalScore | 0.442 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like, what a pooling looked like" | | 1 | "looked like" |
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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 | 1162 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 123 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 21.13 | | std | 16.27 | | cv | 0.77 | | sampleLengths | | 0 | 19 | | 1 | 20 | | 2 | 39 | | 3 | 6 | | 4 | 24 | | 5 | 52 | | 6 | 6 | | 7 | 14 | | 8 | 2 | | 9 | 1 | | 10 | 48 | | 11 | 6 | | 12 | 59 | | 13 | 19 | | 14 | 8 | | 15 | 55 | | 16 | 16 | | 17 | 5 | | 18 | 43 | | 19 | 34 | | 20 | 2 | | 21 | 31 | | 22 | 8 | | 23 | 4 | | 24 | 20 | | 25 | 18 | | 26 | 25 | | 27 | 8 | | 28 | 2 | | 29 | 41 | | 30 | 22 | | 31 | 51 | | 32 | 6 | | 33 | 34 | | 34 | 8 | | 35 | 16 | | 36 | 26 | | 37 | 22 | | 38 | 10 | | 39 | 25 | | 40 | 11 | | 41 | 4 | | 42 | 28 | | 43 | 1 | | 44 | 36 | | 45 | 27 | | 46 | 17 | | 47 | 6 | | 48 | 62 | | 49 | 5 |
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| 97.47% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 90 | | matches | | 0 | "been decommissioned" | | 1 | "was poured" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 125 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 123 | | ratio | 0 | | matches | (empty) | |
| 91.08% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 757 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.05019815059445178 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.013210039630118891 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 123 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 123 | | mean | 9.45 | | std | 7.93 | | cv | 0.839 | | sampleLengths | | 0 | 17 | | 1 | 2 | | 2 | 17 | | 3 | 3 | | 4 | 26 | | 5 | 10 | | 6 | 3 | | 7 | 6 | | 8 | 15 | | 9 | 9 | | 10 | 9 | | 11 | 1 | | 12 | 1 | | 13 | 1 | | 14 | 16 | | 15 | 8 | | 16 | 16 | | 17 | 6 | | 18 | 2 | | 19 | 12 | | 20 | 2 | | 21 | 1 | | 22 | 11 | | 23 | 37 | | 24 | 6 | | 25 | 19 | | 26 | 16 | | 27 | 6 | | 28 | 7 | | 29 | 2 | | 30 | 2 | | 31 | 7 | | 32 | 3 | | 33 | 1 | | 34 | 3 | | 35 | 5 | | 36 | 5 | | 37 | 2 | | 38 | 6 | | 39 | 2 | | 40 | 12 | | 41 | 4 | | 42 | 11 | | 43 | 8 | | 44 | 17 | | 45 | 3 | | 46 | 16 | | 47 | 5 | | 48 | 24 | | 49 | 10 |
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| 84.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5284552845528455 | | totalSentences | 123 | | uniqueOpeners | 65 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 71 | | matches | | 0 | "At least three different people," | | 1 | "Too much for a simple" | | 2 | "Then a sound like fabric" |
| | ratio | 0.042 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 71 | | matches | | 0 | "She pulled out her phone," | | 1 | "She knelt beside a particularly" | | 2 | "Her phone buzzed." | | 3 | "She glanced at the screen." | | 4 | "She'd seen enough crime scenes" | | 5 | "Her torch beam caught something" | | 6 | "She pulled on a glove" | | 7 | "She'd written it off as" | | 8 | "Her phone buzzed again." | | 9 | "I found a match.*" | | 10 | "she called out" |
| | ratio | 0.155 | |
| 44.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 71 | | matches | | 0 | "The blood formed a perfect" | | 1 | "DS Briggs announced with the" | | 2 | "Detective Harlow Quinn crouched beside" | | 3 | "This wasn't one." | | 4 | "Briggs gestured at the empty" | | 5 | "Quinn studied the sigils painted" | | 6 | "She pulled out her phone," | | 7 | "The paint was fresh, maybe" | | 8 | "The chemical tang still hung" | | 9 | "Quinn pointed to a particularly" | | 10 | "Quinn walked the perimeter of" | | 11 | "The Tube station had been" | | 12 | "Footprints in the dust, multiple" | | 13 | "She knelt beside a particularly" | | 14 | "Her phone buzzed." | | 15 | "Morris was three years gone." | | 16 | "She glanced at the screen." | | 17 | "Quinn pocketed the phone and" | | 18 | "The blood bothered her." | | 19 | "She'd seen enough crime scenes" |
| | ratio | 0.831 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 57.14% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 3 | | matches | | 0 | "Quinn felt that familiar tightness in her chest, the sensation that had haunted her since Morris disappeared." | | 1 | "The one that had gotten quietly shuffled into cold cases despite three witnesses and physical evidence that made no logical sense." | | 2 | "Remembered the strange brass key they'd found in his pocket that had disappeared from evidence before it could be catalogued." |
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| 91.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 1 | | matches | | 0 | "the evidence bag pulled slightly, as if magnetized" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "DS Briggs announced (announce)" | | 1 | "Quinn observed (observe)" |
| | dialogueSentences | 48 | | tagDensity | 0.104 | | leniency | 0.208 | | rawRatio | 0.4 | | effectiveRatio | 0.083 | |