| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.583 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1140 | | 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) | |
| 60.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1140 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "footsteps" | | 1 | "rhythmic" | | 2 | "echoing" | | 3 | "methodical" | | 4 | "dancing" | | 5 | "absolutely" | | 6 | "silk" | | 7 | "could feel" |
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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 | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 67 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 73 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1155 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1002 | | uniqueNames | 15 | | maxNameDensity | 0.7 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 2 | | Harlow | 2 | | Quinn | 7 | | Raven | 1 | | Nest | 2 | | Frith | 1 | | Street | 1 | | Camden | 2 | | Three | 1 | | Herrera | 2 | | Seville-born | 1 | | Tomás | 2 | | Morris | 2 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Camden" | | 4 | "Herrera" | | 5 | "Tomás" | | 6 | "Morris" | | 7 | "Saint" | | 8 | "Christopher" |
| | places | | 0 | "Soho" | | 1 | "Nest" | | 2 | "Frith" | | 3 | "Street" | | 4 | "Seville-born" |
| | globalScore | 1 | | windowScore | 1 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like ozone and something sweeter u" | | 1 | "sounded like paper burning" |
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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 | 1155 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 73 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 41.25 | | std | 24.85 | | cv | 0.602 | | sampleLengths | | 0 | 65 | | 1 | 74 | | 2 | 20 | | 3 | 87 | | 4 | 20 | | 5 | 46 | | 6 | 81 | | 7 | 53 | | 8 | 18 | | 9 | 39 | | 10 | 50 | | 11 | 11 | | 12 | 56 | | 13 | 54 | | 14 | 67 | | 15 | 18 | | 16 | 10 | | 17 | 8 | | 18 | 25 | | 19 | 81 | | 20 | 52 | | 21 | 21 | | 22 | 25 | | 23 | 52 | | 24 | 9 | | 25 | 73 | | 26 | 22 | | 27 | 18 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 162 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 1 | | flaggedSentences | 11 | | totalSentences | 73 | | ratio | 0.151 | | matches | | 0 | "Detective Harlow Quinn ran with her coat flapping behind her, boots splashing through puddles that reflected the green glow of a sign she knew too well — The Raven's Nest — as the suspect vaulted a rack of A-boards outside a shuttered kebab shop and disappeared down Frith Street." | | 1 | "Ahead, his footsteps slapped against wet stone, quick and rhythmic — a runner's cadence, she noted, or someone who'd done a lot of running in his life." | | 2 | "Her left hand found her torch; her right rested on the radio at her shoulder." | | 3 | "Water trickled down the steps in thin braids, and her torch beam caught the discarded detritus of decades — a child's shoe, crisp packets, a bicycle frame fused to the wall by rust." | | 4 | "Tomás — she had the name now, pulled it from a file the moment her memory clicked, a paramedic struck off the register two years back, a Herrera, Seville-born, some scandal about unauthorized treatment — Tomás was below her, his footsteps echoing off tiled walls that still wore the ghost of advertising posters." | | 5 | "But the job had also buried DS Morris three years ago, in a case file that still didn't make sense, and the last known address connected to that file — the address she'd never been able to explain to her superintendent — had a green neon sign above its door." | | 6 | "Dozens of them, layered, a market's murmur — haggling, laughter, a child's complaint cut short by a parent's hiss." | | 7 | "Through the bars, the tunnel opened into a cavern that had no business existing beneath Camden — vaulted, vast, strung with lanterns, stalls crowding the space like the pit of some theater." | | 8 | "He had a split lip where he'd clipped himself on the gate, and his face — she catalogued it automatically — wasn't the face of a man relieved to have escaped." | | 9 | "Something moved behind his eyes — calculation, then surrender to some private decision." | | 10 | "Her backup was twenty minutes out, maybe more, and by then whatever this was would have folded up and moved — she could feel it in the warm concrete under her boots, in the wrongness of the air." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 171 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.023391812865497075 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 73 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 73 | | mean | 15.82 | | std | 11.52 | | cv | 0.728 | | sampleLengths | | 0 | 16 | | 1 | 49 | | 2 | 10 | | 3 | 34 | | 4 | 21 | | 5 | 9 | | 6 | 11 | | 7 | 9 | | 8 | 19 | | 9 | 13 | | 10 | 27 | | 11 | 28 | | 12 | 5 | | 13 | 15 | | 14 | 29 | | 15 | 7 | | 16 | 10 | | 17 | 21 | | 18 | 33 | | 19 | 8 | | 20 | 5 | | 21 | 14 | | 22 | 53 | | 23 | 18 | | 24 | 5 | | 25 | 10 | | 26 | 20 | | 27 | 4 | | 28 | 50 | | 29 | 11 | | 30 | 10 | | 31 | 22 | | 32 | 4 | | 33 | 20 | | 34 | 15 | | 35 | 17 | | 36 | 7 | | 37 | 15 | | 38 | 6 | | 39 | 19 | | 40 | 42 | | 41 | 6 | | 42 | 12 | | 43 | 4 | | 44 | 6 | | 45 | 8 | | 46 | 6 | | 47 | 19 | | 48 | 4 | | 49 | 32 |
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| 86.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5342465753424658 | | totalSentences | 73 | | uniqueOpeners | 39 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 65 | | matches | | 0 | "Then the alley opened onto" | | 1 | "Then, slowly, the gates began" |
| | ratio | 0.031 | |
| 96.92% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 65 | | matches | | 0 | "She'd picked him up outside" | | 1 | "She'd made him three weeks" | | 2 | "He cut left at the" | | 3 | "Her left hand found her" | | 4 | "She clipped the radio anyway" | | 5 | "It smelled like ozone and" | | 6 | "She clicked the torch to" | | 7 | "Her light swept across peeling" | | 8 | "Her breath came slow and" | | 9 | "She noticed that with a" | | 10 | "Her voice sounded like paper" | | 11 | "She could see silk and" | | 12 | "Their eyes met through the" | | 13 | "He had a split lip" | | 14 | "It was the face of" | | 15 | "he called, and his accent" | | 16 | "He glanced left and right," | | 17 | "Her radio was dead." | | 18 | "Her backup was twenty minutes" | | 19 | "She reached for her warrant" |
| | ratio | 0.308 | |
| 67.69% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 51 | | totalSentences | 65 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn ran with" | | 2 | "She'd picked him up outside" | | 3 | "She'd made him three weeks" | | 4 | "Tonight he'd finally given her" | | 5 | "The word bounced off wet" | | 6 | "Nobody in Soho answered to" | | 7 | "He cut left at the" | | 8 | "Bin bags split under her" | | 9 | "Quinn slowed at the threshold." | | 10 | "Her left hand found her" | | 11 | "Static answered her, thick and" | | 12 | "She clipped the radio anyway" | | 13 | "The stairs descended in a" | | 14 | "Water trickled down the steps" | | 15 | "The air coming up from" | | 16 | "It smelled like ozone and" | | 17 | "Tomás — she had the" | | 18 | "Quinn stood at the top" | | 19 | "Everything in her said wait." |
| | ratio | 0.785 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 27.03% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 6 | | matches | | 0 | "Detective Harlow Quinn ran with her coat flapping behind her, boots splashing through puddles that reflected the green glow of a sign she knew too well — The Ra…" | | 1 | "Ahead, his footsteps slapped against wet stone, quick and rhythmic — a runner's cadence, she noted, or someone who'd done a lot of running in his life." | | 2 | "Then the alley opened onto the litter-strewn mouth of the old Camden cut, and the chain-link gate that had been welded shut since the nineties stood ajar, swing…" | | 3 | "The stairs descended in a spiral of green-painted concrete, the kind of institutional color that had probably looked cheerful in 1965." | | 4 | "Through the bars, the tunnel opened into a cavern that had no business existing beneath Camden — vaulted, vast, strung with lanterns, stalls crowding the space …" | | 5 | "She could see silk and smoke, jars of things that moved, a butcher's counter displaying cuts of meat in colors meat should never be." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |