| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1442 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 41.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1442 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "tension" | | 2 | "weight" | | 3 | "familiar" | | 4 | "footsteps" | | 5 | "pulse" | | 6 | "echoing" | | 7 | "chill" | | 8 | "pulsed" | | 9 | "echoed" | | 10 | "could feel" | | 11 | "structure" | | 12 | "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 | 1 | | narrationSentences | 107 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 107 | | filterMatches | | | hedgeMatches | | |
| 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 | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1451 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 1371 | | uniqueNames | 18 | | maxNameDensity | 1.31 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Vauxhall | 1 | | Harlow | 18 | | Quinn | 2 | | Raven | 1 | | Nest | 3 | | Saint | 1 | | Christopher | 1 | | Webb | 15 | | Met | 1 | | Camden | 2 | | Town | 1 | | Tube | 1 | | Northern | 2 | | Line | 2 | | Veil | 3 | | Market | 5 | | Morris | 3 | | London | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Webb" | | 5 | "Met" | | 6 | "Line" | | 7 | "Market" | | 8 | "Morris" |
| | places | | 0 | "Vauxhall" | | 1 | "Raven" | | 2 | "Camden" | | 3 | "Town" | | 4 | "Tube" | | 5 | "Veil" | | 6 | "London" |
| | globalScore | 0.844 | | windowScore | 0.833 | |
| 89.02% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 82 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite running, his shoulders hunched against the weather" | | 1 | "fabrics that seemed to drink the amber light rather than reflect it" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.689 | | wordCount | 1451 | | matches | | 0 | "not by people, but by tokens" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 112 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 39.22 | | std | 22.58 | | cv | 0.576 | | sampleLengths | | 0 | 63 | | 1 | 7 | | 2 | 88 | | 3 | 47 | | 4 | 7 | | 5 | 72 | | 6 | 23 | | 7 | 44 | | 8 | 74 | | 9 | 44 | | 10 | 9 | | 11 | 28 | | 12 | 44 | | 13 | 79 | | 14 | 18 | | 15 | 59 | | 16 | 14 | | 17 | 43 | | 18 | 19 | | 19 | 30 | | 20 | 19 | | 21 | 4 | | 22 | 56 | | 23 | 45 | | 24 | 34 | | 25 | 20 | | 26 | 32 | | 27 | 61 | | 28 | 66 | | 29 | 53 | | 30 | 31 | | 31 | 64 | | 32 | 51 | | 33 | 10 | | 34 | 55 | | 35 | 16 | | 36 | 22 |
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| 98.70% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 107 | | matches | | 0 | "were won" | | 1 | "being hunted" | | 2 | "were lined" |
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| 86.04% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 234 | | matches | | 0 | "wasn’t heading" | | 1 | "was heading" | | 2 | "was heading" | | 3 | "was running" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 112 | | ratio | 0.08 | | matches | | 0 | "Three warrants outstanding, suspected in a string of burglaries that had escalated into something far more interesting — break-ins at four separate antiquities dealers across the city, each one specializing in objects the Met didn’t officially acknowledge existed." | | 1 | "Eighteen years on the force had taught her that chases were won in the first thirty seconds — the window before the quarry realizes they’re being hunted." | | 2 | "Webb was young, maybe twenty-five, but he ran like someone who’d spent his life running — inefficient, panicked, all elbows and wasted motion." | | 3 | "Harlow saw the move for what it was — he wasn’t heading for the trains." | | 4 | "In the dim light, his face was gaunt with fear — not fear of her, she realized with a chill." | | 5 | "The entrance to the Veil Market was guarded — not by people, but by tokens." | | 6 | "She’d lost Morris to questions exactly like this one — questions about what lurked beneath the city, about the transactions that happened in the spaces between the world she knew and the world that existed just beneath the surface." | | 7 | "The air hummed with the murmur of voices and the clink of currency — not coins, weighing bulbs of bioluminescent fungi in his palm." | | 8 | "Webb was ahead of her, pushing through the crowd toward a structure at the far end of the cavern — a pavilion draped in black silk, guarded by two figures who were human-shaped but wrong in ways Harlow’s mind skittered away from." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 198 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.020202020202020204 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.005050505050505051 | |
| 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 | 12.96 | | std | 8.92 | | cv | 0.689 | | sampleLengths | | 0 | 7 | | 1 | 23 | | 2 | 33 | | 3 | 7 | | 4 | 23 | | 5 | 19 | | 6 | 21 | | 7 | 18 | | 8 | 7 | | 9 | 4 | | 10 | 7 | | 11 | 11 | | 12 | 25 | | 13 | 7 | | 14 | 7 | | 15 | 16 | | 16 | 9 | | 17 | 2 | | 18 | 38 | | 19 | 9 | | 20 | 14 | | 21 | 5 | | 22 | 7 | | 23 | 16 | | 24 | 16 | | 25 | 7 | | 26 | 26 | | 27 | 14 | | 28 | 27 | | 29 | 13 | | 30 | 8 | | 31 | 8 | | 32 | 15 | | 33 | 9 | | 34 | 3 | | 35 | 9 | | 36 | 8 | | 37 | 6 | | 38 | 2 | | 39 | 6 | | 40 | 23 | | 41 | 12 | | 42 | 3 | | 43 | 23 | | 44 | 15 | | 45 | 18 | | 46 | 23 | | 47 | 18 | | 48 | 16 | | 49 | 14 |
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| 57.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.375 | | totalSentences | 112 | | uniqueOpeners | 42 | |
| 33.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 101 | | matches | | 0 | "Somewhere behind her, in the" |
| | ratio | 0.01 | |
| 97.23% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 101 | | matches | | 0 | "It sheeted against the windscreen" | | 1 | "She’d been sitting there for" | | 2 | "He’d been a paramedic then," | | 3 | "She remembered the way he’d" | | 4 | "She’d been wearing it the" | | 5 | "She’d been trying to catch" | | 6 | "He moved east on foot," | | 7 | "She’d worn the wrong coat," | | 8 | "She kept to the shadows," | | 9 | "He’d spotted her." | | 10 | "It happened sometimes, even when" | | 11 | "Her boots splashed through ankle-deep" | | 12 | "She gained ground." | | 13 | "He was heading for the" | | 14 | "She’d heard rumors about what" | | 15 | "She could hear Webb’s footsteps" | | 16 | "He was tiring." | | 17 | "He stood at the edge" | | 18 | "She slowed to a walk," | | 19 | "He turned to face her." |
| | ratio | 0.307 | |
| 24.36% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 101 | | matches | | 0 | "The rain hadn’t let up" | | 1 | "It sheeted against the windscreen" | | 2 | "Detective Harlow Quinn sat motionless" | | 3 | "She’d been sitting there for" | | 4 | "The green neon sign above" | | 5 | "Tomás had told her about" | | 6 | "He’d been a paramedic then," | | 7 | "She remembered the way he’d" | | 8 | "Harlow checked her watch." | | 9 | "Leather strap, worn soft at" | | 10 | "Morris had given it to" | | 11 | "She’d been wearing it the" | | 12 | "The door to the Nest" | | 13 | "A figure slipped out into" | | 14 | "Harlow recognized the gait before" | | 15 | "She’d been trying to catch" | | 16 | "The fact that he kept" | | 17 | "Webb glanced left, then right." | | 18 | "Rain plastered his hood to" | | 19 | "He moved east on foot," |
| | ratio | 0.871 | |
| 99.01% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 101 | | matches | | 0 | "Even then, he’d been warning" | | 1 | "If Harlow wanted answers about" |
| | ratio | 0.02 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 8 | | matches | | 0 | "The green neon sign above the bar bled color into the puddled pavement, a sickly emerald that reminded her of old hospital corridors." | | 1 | "Three warrants outstanding, suspected in a string of burglaries that had escalated into something far more interesting — break-ins at four separate antiquities …" | | 2 | "Webb was young, maybe twenty-five, but he ran like someone who’d spent his life running — inefficient, panicked, all elbows and wasted motion." | | 3 | "He stood at the edge of the platform, his chest heaving, staring at something Harlow couldn’t yet see." | | 4 | "It sloped downward at an angle the engineers who built the Northern Line would never have sanctioned, and from somewhere deep within it came a faint, amber glow…" | | 5 | "She’d lost Morris to questions exactly like this one — questions about what lurked beneath the city, about the transactions that happened in the spaces between …" | | 6 | "If Harlow wanted answers about what had killed Morris, about the network that connected the supernatural crime she’d been tracking for years, this was her chanc…" | | 7 | "Webb was ahead of her, pushing through the crowd toward a structure at the far end of the cavern — a pavilion draped in black silk, guarded by two figures who w…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |