| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 1 | | adverbTags | | 0 | "she shouted back [back]" |
| | dialogueSentences | 7 | | tagDensity | 0.714 | | leniency | 1 | | rawRatio | 0.2 | | effectiveRatio | 0.2 | |
| 93.04% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1437 | | totalAiIsmAdverbs | 2 | | 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) | |
| 93.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1437 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 99 | | matches | (empty) | |
| 99.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 99 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 66 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 8 | | markdownWords | 36 | | totalWords | 1451 | | ratio | 0.025 | | matches | | 0 | "Officer pursuing male, former paramedic, no fixed charge, direction of travel: a closed Tube station that doesn't exist." | | 1 | "corpse" | | 2 | "candles" | | 3 | "incense" | | 4 | "anything" | | 5 | "the Market, the Market, it moves when the moon does" | | 6 | "miscellaneous pendant" | | 7 | "stop mattering" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 1416 | | uniqueNames | 25 | | maxNameDensity | 0.56 | | worstName | "Herrera" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Herrera" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 7 | | Raven | 2 | | Nest | 3 | | Tomás | 1 | | Herrera | 8 | | Saint | 1 | | Christopher | 1 | | Wardour | 1 | | Street | 3 | | Oxford | 1 | | Centre | 1 | | Point | 1 | | Tottenham | 1 | | Court | 1 | | Road | 1 | | Tube | 1 | | Morris | 5 | | Goodge | 1 | | Spanish | 1 | | English | 1 | | Camden | 1 | | Northern | 1 | | Market | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Nest" | | 3 | "Tomás" | | 4 | "Herrera" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Morris" |
| | places | | 0 | "Raven" | | 1 | "Wardour" | | 2 | "Street" | | 3 | "Oxford" | | 4 | "Centre" | | 5 | "Point" | | 6 | "Tottenham" | | 7 | "Court" | | 8 | "Road" | | 9 | "Goodge" | | 10 | "Spanish" | | 11 | "English" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1451 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 101 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 39.22 | | std | 30.15 | | cv | 0.769 | | sampleLengths | | 0 | 26 | | 1 | 75 | | 2 | 53 | | 3 | 74 | | 4 | 11 | | 5 | 43 | | 6 | 3 | | 7 | 2 | | 8 | 106 | | 9 | 38 | | 10 | 25 | | 11 | 84 | | 12 | 8 | | 13 | 32 | | 14 | 16 | | 15 | 22 | | 16 | 62 | | 17 | 81 | | 18 | 22 | | 19 | 9 | | 20 | 78 | | 21 | 35 | | 22 | 32 | | 23 | 77 | | 24 | 1 | | 25 | 92 | | 26 | 9 | | 27 | 64 | | 28 | 69 | | 29 | 14 | | 30 | 36 | | 31 | 19 | | 32 | 9 | | 33 | 3 | | 34 | 79 | | 35 | 27 | | 36 | 15 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 16.51% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 218 | | matches | | 0 | "was earning" | | 1 | "was vaulting" | | 2 | "wasn't running" | | 3 | "was running" | | 4 | "was waiting" | | 5 | "was going" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 1 | | flaggedSentences | 14 | | totalSentences | 101 | | ratio | 0.139 | | matches | | 0 | "He paused under the sign to pull up his collar, and the neon caught the small gold circle at his throat — Saint Christopher, patron of travelers." | | 1 | "He did something worse — he slowed." | | 2 | "There — the white flash of a trainer sole in a puddle, up the steps of Centre Point, gone left toward Tottenham Court Road." | | 3 | "He shouted something over his shoulder as they crossed into the dark stretch past Goodge Street — Spanish, fast, and then, in English: \"Detective! You do not want what is down there!\"" | | 4 | "Not fear — laughter, ragged and almost kind, like she was the one in danger." | | 5 | "He stopped at a rusted gate in a brick wall she'd have sworn wasn't there when she'd walked this street last month — a wall between a shuttered kebab shop and a boarded bookmaker's, a gate behind a curtain of ivy." | | 6 | "Concrete steps descending into a station that had no right to be there — no sign, no roundel, just the bones of the Northern line, some sealed spur the maps had forgotten." | | 7 | "And from below — sound." | | 8 | "No signal — she'd checked, her phone a dead black brick in her pocket." | | 9 | "An underground market that moved every full moon; she had that phrase from an interview transcript, some junkie in A&E babbling about *the Market, the Market, it moves when the moon does*, and she'd filed it under nonsense because filing it anywhere else meant filing Morris under nonsense too." | | 10 | "Its face was like a photograph left out in the rain — features run and blurred, the suggestion of eyes, the suggestion of patience." | | 11 | "Morris had stood at a threshold like this one — she was sure of it now, sure in the marrow — and he had gone in, and whatever took him had never let him out." | | 12 | "It closed its fingers, and the token didn't so much vanish as *stop mattering*, and the blurred face inclined — acknowledgment, or appetite, she couldn't tell which." | | 13 | "She went down the stairs into light that didn't belong to any lamp she knew — a whole abandoned station hollowed out and burning with it, platform edges crowded with stalls, bottled things glowing like trapped weather, a heart beating slow and red in a jar of clear fluid, alchemists trading under strings of lanterns, brokers whispering into the ears of buyers who were not entirely human." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1407 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 43 | | adverbRatio | 0.030561478322672354 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.004975124378109453 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 14.37 | | std | 13.71 | | cv | 0.954 | | sampleLengths | | 0 | 26 | | 1 | 5 | | 2 | 26 | | 3 | 44 | | 4 | 16 | | 5 | 27 | | 6 | 3 | | 7 | 7 | | 8 | 32 | | 9 | 8 | | 10 | 34 | | 11 | 3 | | 12 | 8 | | 13 | 5 | | 14 | 7 | | 15 | 31 | | 16 | 3 | | 17 | 2 | | 18 | 22 | | 19 | 36 | | 20 | 9 | | 21 | 39 | | 22 | 6 | | 23 | 32 | | 24 | 1 | | 25 | 24 | | 26 | 8 | | 27 | 7 | | 28 | 1 | | 29 | 1 | | 30 | 5 | | 31 | 21 | | 32 | 12 | | 33 | 29 | | 34 | 6 | | 35 | 2 | | 36 | 32 | | 37 | 16 | | 38 | 2 | | 39 | 5 | | 40 | 15 | | 41 | 3 | | 42 | 47 | | 43 | 7 | | 44 | 5 | | 45 | 41 | | 46 | 40 | | 47 | 5 | | 48 | 3 | | 49 | 4 |
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| 63.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.44 | | totalSentences | 100 | | uniqueOpeners | 44 | |
| 80.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 83 | | matches | | 0 | "Then he ran." | | 1 | "Then he went down." |
| | ratio | 0.024 | |
| 51.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 83 | | matches | | 0 | "She'd been there since nine." | | 1 | "He had a medical bag" | | 2 | "He paused under the sign" | | 3 | "She'd seen Herrera come out" | | 4 | "She didn't have a word" | | 5 | "She gave him half a" | | 6 | "He didn't run at first." | | 7 | "He did something worse —" | | 8 | "His canvas jacket flashed grey" | | 9 | "She put her hand on" | | 10 | "Her breath was a knife" | | 11 | "She thought, distantly, professionally, about" | | 12 | "They'd section her, maybe, the" | | 13 | "He shouted something over his" | | 14 | "she shouted back, and her" | | 15 | "He was running toward something." | | 16 | "He stopped at a rusted" | | 17 | "He hauled it open on" | | 18 | "She reached the gate ten" | | 19 | "It smelled of ozone and" |
| | ratio | 0.422 | |
| 80.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 83 | | matches | | 0 | "The rain came down like" | | 1 | "She'd been there since nine." | | 2 | "He had a medical bag" | | 3 | "He paused under the sign" | | 4 | "Quinn almost smiled." | | 5 | "The saint was earning his" | | 6 | "She'd seen Herrera come out" | | 7 | "People went in there and" | | 8 | "She didn't have a word" | | 9 | "Herrera headed north." | | 10 | "She gave him half a" | | 11 | "He didn't run at first." | | 12 | "He did something worse —" | | 13 | "Soho at midnight was all" | | 14 | "Herrera cut left off Wardour" | | 15 | "His canvas jacket flashed grey" | | 16 | "The medallion flew up against" | | 17 | "A cab laid on its" | | 18 | "She put her hand on" | | 19 | "There — the white flash" |
| | ratio | 0.759 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 83 | | matches | | 0 | "To the night, maybe." | | 1 | "To the saint at his" |
| | ratio | 0.024 | |
| 6.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 8 | | matches | | 0 | "She'd seen Herrera come out of the back of the bar an hour ago, the back that didn't exist, the bookshelf-lined corridor that wasn't on any plan of the building…" | | 1 | "Herrera cut left off Wardour Street, young legs eating the ground, and she went after him with everything her forty-one years would give her, which was less tha…" | | 2 | "The medallion flew up against his throat as he vaulted a barrier outside a roadwork site, and then she was vaulting it too, boots skidding on wet plank, shoulde…" | | 3 | "*Officer pursuing male, former paramedic, no fixed charge, direction of travel: a closed Tube station that doesn't exist.* They'd pull her." | | 4 | "Concrete steps descending into a station that had no right to be there — no sign, no roundel, just the bones of the Northern line, some sealed spur the maps had…" | | 5 | "Voices, layered, in languages that didn't friction against each other the way real languages did." | | 6 | "An underground market that moved every full moon; she had that phrase from an interview transcript, some junkie in A&E babbling about *the Market, the Market, i…" | | 7 | "She went down the stairs into light that didn't belong to any lamp she knew — a whole abandoned station hollowed out and burning with it, platform edges crowded…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "He shouted (shout)" | | 1 | "she shouted back (shout)" |
| | dialogueSentences | 7 | | tagDensity | 0.714 | | leniency | 1 | | rawRatio | 0.4 | | effectiveRatio | 0.4 | |