| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.615 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1189 | | 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) | |
| 87.38% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1189 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "electric" | | 1 | "could feel" | | 2 | "pulse" |
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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 | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 82 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1201 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1098 | | uniqueNames | 16 | | maxNameDensity | 0.73 | | worstName | "Herrera" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Herrera" | | discoveredNames | | Soho | 1 | | Tomás | 1 | | Herrera | 8 | | Saint | 1 | | Christopher | 1 | | Morris | 3 | | Greek | 1 | | Street | 1 | | Camden | 1 | | Underground | 1 | | Tube | 1 | | Harl | 1 | | Metropolitan | 1 | | Police | 1 | | Edwardian | 1 | | Quinn | 5 |
| | persons | | 0 | "Tomás" | | 1 | "Herrera" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Morris" | | 5 | "Police" | | 6 | "Quinn" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 65.25% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 2 | | matches | | 0 | "something like a livestock market on a summe" | | 1 | "ry fee unpaid, apparently, and still admitted" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.833 | | wordCount | 1201 | | matches | | 0 | "not by watching the runner but by watching what the runner watched" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 87 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 42.89 | | std | 29.62 | | cv | 0.69 | | sampleLengths | | 0 | 26 | | 1 | 82 | | 2 | 15 | | 3 | 90 | | 4 | 63 | | 5 | 67 | | 6 | 8 | | 7 | 67 | | 8 | 38 | | 9 | 68 | | 10 | 39 | | 11 | 8 | | 12 | 95 | | 13 | 9 | | 14 | 4 | | 15 | 108 | | 16 | 41 | | 17 | 55 | | 18 | 60 | | 19 | 7 | | 20 | 49 | | 21 | 32 | | 22 | 54 | | 23 | 16 | | 24 | 53 | | 25 | 32 | | 26 | 7 | | 27 | 8 |
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| 92.43% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 82 | | matches | | 0 | "been taught" | | 1 | "was bolted" | | 2 | "been curtained" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 182 | | matches | | 0 | "were checking" | | 1 | "was still coming" | | 2 | "was weighing" | | 3 | "was buying" | | 4 | "was accumulating" | | 5 | "was holding" | | 6 | "was examining" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 87 | | ratio | 0.115 | | matches | | 0 | "Quinn kept him in sight the way she'd been taught eighteen years ago — not by watching the runner but by watching what the runner watched." | | 1 | "She'd seen him twice before, both times at the periphery of cases that had ended badly — cases that ended with DS Morris's name on a plaque in the lobby and no body and no answers." | | 2 | "Below her, Herrera paused on the landing, looked back up, and — this was the strange part — waited." | | 3 | "She could feel it — a draft rising warm off the stairs, carrying the smell of candle wax and cut herbs and something animal underneath, something like a livestock market on a summer day." | | 4 | "Her left hand checked the cuff of the watch Morris had given her — you'll need to know when the night ends, Harl — and the worn leather was slick with rain but the watch still ticked." | | 5 | "The walls had been curtained, in places — heavy drapes hung between the old advertising frames, and behind the gaps she saw stalls." | | 6 | "Two figures in dark coats by a brazier did turn, and one of them held up a small object toward her — a token, white and carved, some kind of bone." | | 7 | "The market opened into the old platform hall, and it was vast — a bazaar built into a cathedral of Edwardian tile and iron, lamps strung on wires between pillars, hundreds of people and people-shaped things trading in low voices." | | 8 | "He was also, she noticed, holding out his left arm, sleeve rolled back, the long knife scar along his forearm livid under the lamplight — and the figure was examining it." | | 9 | "Herrera's voice carried in fragments over the noise — \"...the same pattern... three years... it's not healing wrong, it's healing true—\" And then he stopped talking, and turned his head, and looked directly at her." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1090 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.029357798165137616 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0045871559633027525 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 13.8 | | std | 11.04 | | cv | 0.8 | | sampleLengths | | 0 | 26 | | 1 | 26 | | 2 | 6 | | 3 | 12 | | 4 | 38 | | 5 | 7 | | 6 | 8 | | 7 | 3 | | 8 | 4 | | 9 | 23 | | 10 | 36 | | 11 | 16 | | 12 | 8 | | 13 | 23 | | 14 | 27 | | 15 | 13 | | 16 | 41 | | 17 | 7 | | 18 | 2 | | 19 | 17 | | 20 | 8 | | 21 | 18 | | 22 | 10 | | 23 | 18 | | 24 | 6 | | 25 | 15 | | 26 | 19 | | 27 | 9 | | 28 | 10 | | 29 | 11 | | 30 | 27 | | 31 | 16 | | 32 | 3 | | 33 | 4 | | 34 | 7 | | 35 | 5 | | 36 | 34 | | 37 | 8 | | 38 | 18 | | 39 | 37 | | 40 | 2 | | 41 | 17 | | 42 | 12 | | 43 | 9 | | 44 | 5 | | 45 | 4 | | 46 | 4 | | 47 | 9 | | 48 | 23 | | 49 | 2 |
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| 67.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.45977011494252873 | | totalSentences | 87 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 72 | | matches | | 0 | "Of course he didn't." | | 1 | "Then the lights below him" | | 2 | "Somewhere a musician played a" | | 3 | "Somewhere something laughed with a" |
| | ratio | 0.056 | |
| 53.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 72 | | matches | | 0 | "He checked left before the" | | 1 | "He didn't check the right," | | 2 | "Her voice cracked against the" | | 3 | "He didn't slow." | | 4 | "She'd seen him twice before," | | 5 | "She'd spent two years finding" | | 6 | "He cut across Greek Street," | | 7 | "She'd stopped believing that last" | | 8 | "She hit the gate with" | | 9 | "It was the oldest rule" | | 10 | "Her radio was soaked dead" | | 11 | "Her backup was a thirty-minute" | | 12 | "They were a warm amber," | | 13 | "She knew this stretch." | | 14 | "She could feel it —" | | 15 | "Her left hand checked the" | | 16 | "She drew her baton, thought" | | 17 | "she said to nobody" | | 18 | "She took the stairs." | | 19 | "She shook her head." |
| | ratio | 0.417 | |
| 78.06% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 72 | | matches | | 0 | "The rain came down in" | | 1 | "Quinn kept him in sight" | | 2 | "He checked left before the" | | 3 | "He didn't check the right," | | 4 | "That told her he'd planned" | | 5 | "Her voice cracked against the" | | 6 | "He didn't slow." | | 7 | "Nobody with a Saint Christopher" | | 8 | "She'd seen him twice before," | | 9 | "Herrera's face had been in" | | 10 | "She'd spent two years finding" | | 11 | "He cut across Greek Street," | | 12 | "The city was empty at" | | 13 | "She'd stopped believing that last" | | 14 | "Herrera ducked down a service" | | 15 | "She hit the gate with" | | 16 | "Quinn stopped at the top" | | 17 | "It was the oldest rule" | | 18 | "Her radio was soaked dead" | | 19 | "Her backup was a thirty-minute" |
| | ratio | 0.764 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 72 | | matches | | 0 | "As if he were checking" | | 1 | "As if the running had" | | 2 | "If the Metropolitan Police had" | | 3 | "If they didn't, the pistol" |
| | ratio | 0.056 | |
| 89.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 3 | | matches | | 0 | "The rain came down in sheets over Soho, turning the neon to smeared watercolor, and Tomás Herrera ran like a man who had done this before." | | 1 | "The city was empty at this hour except for the drunk and the desperate and the ones who worked the dark hours because daylight would kill them." | | 2 | "They were a warm amber, lamplight amber, and they lit a tunnel that hadn't been in the survey of Camden Underground she'd memorized on the drive over." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "Herrera said, not unkindly" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0 | | effectiveRatio | 0 | |