| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "she asked quietly [quietly]" |
| | dialogueSentences | 15 | | tagDensity | 0.533 | | leniency | 1 | | rawRatio | 0.25 | | effectiveRatio | 0.25 | |
| 83.93% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1556 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "perfectly" | | 1 | "slightly" | | 2 | "gently" | | 3 | "suddenly" | | 4 | "softly" |
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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) | |
| 90.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1556 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "streaming" | | 1 | "structure" | | 2 | "silk" |
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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 | 2 | | narrationSentences | 105 | | matches | | 0 | "was surprised" | | 1 | "was surprised" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 105 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 112 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1568 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 1431 | | uniqueNames | 18 | | maxNameDensity | 0.77 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 11 | | Raven | 1 | | Nest | 1 | | Frith | 1 | | Street | 2 | | Dean | 1 | | Danny | 2 | | Kessler | 8 | | Fitzrovia | 2 | | Peckham | 1 | | Morris | 5 | | Soho | 1 | | Camden | 2 | | Tube | 2 | | Static | 1 | | London | 2 | | Highlands | 1 | | Tuesday | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Danny" | | 2 | "Kessler" | | 3 | "Morris" | | 4 | "Static" |
| | places | | 0 | "Raven" | | 1 | "Frith" | | 2 | "Street" | | 3 | "Dean" | | 4 | "Fitzrovia" | | 5 | "Peckham" | | 6 | "Soho" | | 7 | "Camden" | | 8 | "London" | | 9 | "Highlands" |
| | globalScore | 1 | | windowScore | 1 | |
| 86.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like breathing" | | 1 | "quite music, a laugh that went on too long, the clink of glass and the soft percussion of commerce conducted by people who should not exist" |
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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 | 1568 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 112 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 40.21 | | std | 30.5 | | cv | 0.759 | | sampleLengths | | 0 | 18 | | 1 | 70 | | 2 | 2 | | 3 | 59 | | 4 | 78 | | 5 | 68 | | 6 | 21 | | 7 | 17 | | 8 | 68 | | 9 | 28 | | 10 | 39 | | 11 | 11 | | 12 | 47 | | 13 | 14 | | 14 | 68 | | 15 | 42 | | 16 | 20 | | 17 | 10 | | 18 | 78 | | 19 | 84 | | 20 | 29 | | 21 | 54 | | 22 | 27 | | 23 | 1 | | 24 | 11 | | 25 | 29 | | 26 | 79 | | 27 | 35 | | 28 | 95 | | 29 | 24 | | 30 | 3 | | 31 | 7 | | 32 | 121 | | 33 | 23 | | 34 | 93 | | 35 | 45 | | 36 | 8 | | 37 | 8 | | 38 | 34 |
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| 98.58% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 105 | | matches | | 0 | "was surprised" | | 1 | "was surprised" |
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| 83.04% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 228 | | matches | | 0 | "was heading" | | 1 | "was going" | | 2 | "was doing" | | 3 | "was still killing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 112 | | ratio | 0.098 | | matches | | 0 | "Her target was twenty meters ahead — a wiry man in a gray hoodie who had bolted the moment she'd shown her warrant card outside the Raven's Nest." | | 1 | "Not the open stations — Quinn knew this stretch, knew the disused station that sat boarded up off the high road, a husk the city had forgotten to demolish." | | 2 | "That was impossible — she was in the middle of London, not the Highlands." | | 3 | "There was a gap in the boards she would have sworn hadn't been there when she'd walked past last month — a man-sized tear in the plywood, black as a throat behind it." | | 4 | "The ticket hall was a cavern of peeling green tile, and it was not abandoned — that was the first wrong thing, the thing that made her stop dead with her hand halfway to her collar." | | 5 | "Kessler was twenty meters in, moving fast between the stalls, and he was doing something with his hands as he walked — digging in his pocket." | | 6 | "Kessler was at a stall now, exchanging something — a small bone disc, white as a knuckle — with a stallholder who waved him through a curtain of chains into the deeper market." | | 7 | "The bearded man looked at her the way men looked at weather — with a kind of patient indifference." | | 8 | "Beyond it the market wound away into the dark of the old platform tunnels, and she could hear things down there — music that wasn't quite music, a laugh that went on too long, the clink of glass and the soft percussion of commerce conducted by people who should not exist." | | 9 | "It moved, she understood suddenly, the way fog moves, the way guilt moves — a market that was never in the same place when you came looking." | | 10 | "Then her fingers found the leather strap of her watch — Morris's watch, actually, the one he'd worn the night he died, the one she'd taken from the evidence bag and never signed back out." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1426 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.0273492286115007 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.011220196353436185 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 112 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 112 | | mean | 14 | | std | 11.35 | | cv | 0.811 | | sampleLengths | | 0 | 18 | | 1 | 28 | | 2 | 42 | | 3 | 2 | | 4 | 17 | | 5 | 6 | | 6 | 36 | | 7 | 14 | | 8 | 15 | | 9 | 27 | | 10 | 5 | | 11 | 17 | | 12 | 19 | | 13 | 4 | | 14 | 45 | | 15 | 6 | | 16 | 1 | | 17 | 14 | | 18 | 8 | | 19 | 9 | | 20 | 27 | | 21 | 6 | | 22 | 29 | | 23 | 3 | | 24 | 3 | | 25 | 15 | | 26 | 13 | | 27 | 15 | | 28 | 5 | | 29 | 5 | | 30 | 14 | | 31 | 11 | | 32 | 8 | | 33 | 33 | | 34 | 6 | | 35 | 14 | | 36 | 12 | | 37 | 2 | | 38 | 2 | | 39 | 8 | | 40 | 17 | | 41 | 11 | | 42 | 9 | | 43 | 7 | | 44 | 42 | | 45 | 6 | | 46 | 14 | | 47 | 10 | | 48 | 10 | | 49 | 36 |
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| 56.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.4017857142857143 | | totalSentences | 112 | | uniqueOpeners | 45 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 100 | | matches | | 0 | "Then she thought of Morris" | | 1 | "Too many people for a" | | 2 | "Then her fingers found the" |
| | ratio | 0.03 | |
| 80.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 100 | | matches | | 0 | "Her target was twenty meters" | | 1 | "He cut left across Dean" | | 2 | "Her coat was already soaked" | | 3 | "She was fit for forty-one." | | 4 | "His name was Danny Kessler," | | 5 | "She only knew that the" | | 6 | "She'd seen silver like that" | | 7 | "She shoved it down where" | | 8 | "He was heading for the" | | 9 | "she gasped into her radio," | | 10 | "She glanced at the radio." | | 11 | "She dropped the radio back" | | 12 | "He slipped through sideways and" | | 13 | "She had drilled rookies out" | | 14 | "You go home at the" | | 15 | "She was sure of it" | | 16 | "she said quietly, and went" | | 17 | "He held out one palm," | | 18 | "He didn't move" | | 19 | "His palm stayed out, scarred" |
| | ratio | 0.35 | |
| 65.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 79 | | totalSentences | 100 | | matches | | 0 | "The rain came down like" | | 1 | "Her target was twenty meters" | | 2 | "The bar's green neon sign" | | 3 | "The words came out by" | | 4 | "The man didn't even glance" | | 5 | "He cut left across Dean" | | 6 | "The worn leather watch on" | | 7 | "Her coat was already soaked" | | 8 | "She was fit for forty-one." | | 9 | "The man ahead of her" | | 10 | "His name was Danny Kessler," | | 11 | "Quinn didn't know what." | | 12 | "She only knew that the" | | 13 | "She'd seen silver like that" | | 14 | "That thought had no business" | | 15 | "She shoved it down where" | | 16 | "Kessler vaulted the barriers at" | | 17 | "He was heading for the" | | 18 | "Nobody went there." | | 19 | "she gasped into her radio," |
| | ratio | 0.79 | |
| 50.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 100 | | matches | | 0 | "Even at this distance, through" |
| | ratio | 0.01 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 6 | | matches | | 0 | "Her target was twenty meters ahead — a wiry man in a gray hoodie who had bolted the moment she'd shown her warrant card outside the Raven's Nest." | | 1 | "Not the open stations — Quinn knew this stretch, knew the disused station that sat boarded up off the high road, a husk the city had forgotten to demolish." | | 2 | "The ticket hall was a cavern of peeling green tile, and it was not abandoned — that was the first wrong thing, the thing that made her stop dead with her hand h…" | | 3 | "Kessler was at a stall now, exchanging something — a small bone disc, white as a knuckle — with a stallholder who waved him through a curtain of chains into the…" | | 4 | "Beyond it the market wound away into the dark of the old platform tunnels, and she could hear things down there — music that wasn't quite music, a laugh that we…" | | 5 | "She was one unarmed woman in a place with no law she recognized, no backup, no comms, no exit she could guarantee, and somewhere in that dark was the man who co…" |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | |
| 16.67% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "she gasped (gasp)" | | 1 | "he repeated (repeat)" |
| | dialogueSentences | 15 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.333 | | effectiveRatio | 0.267 | |