| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.75 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 82.05% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1393 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "very" | | 1 | "carefully" | | 2 | "perfectly" |
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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) | |
| 71.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1393 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "flickered" | | 1 | "pulse" | | 2 | "weight" | | 3 | "charged" | | 4 | "footsteps" | | 5 | "electric" | | 6 | "structure" |
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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 | 94 | | matches | (empty) | |
| 97.26% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 94 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 11 | | totalWords | 1399 | | ratio | 0.008 | | matches | | 0 | "oi" | | 1 | "He's not running home. He's not running to a lawyer." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1388 | | uniqueNames | 21 | | maxNameDensity | 0.72 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Morris" | | discoveredNames | | Quinn | 10 | | Meard | 1 | | Street | 5 | | Herrera | 7 | | Seville-born | 1 | | Europe | 1 | | Saint | 1 | | Christopher | 1 | | Oxford | 1 | | Hendon | 1 | | Tottenham | 1 | | Court | 1 | | Road | 1 | | Friday | 1 | | Escalator | 1 | | Silas | 1 | | Morris | 5 | | February | 1 | | Crescent | 1 | | Camden | 1 | | Town | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Herrera" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Silas" | | 5 | "Morris" |
| | places | | 0 | "Meard" | | 1 | "Street" | | 2 | "Seville-born" | | 3 | "Europe" | | 4 | "Oxford" | | 5 | "Hendon" | | 6 | "Tottenham" | | 7 | "Court" | | 8 | "Road" | | 9 | "February" | | 10 | "Crescent" | | 11 | "Camden" | | 12 | "Town" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | 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 | 1399 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 95 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 49.96 | | std | 32.61 | | cv | 0.653 | | sampleLengths | | 0 | 107 | | 1 | 3 | | 2 | 77 | | 3 | 73 | | 4 | 90 | | 5 | 8 | | 6 | 102 | | 7 | 20 | | 8 | 22 | | 9 | 86 | | 10 | 88 | | 11 | 76 | | 12 | 13 | | 13 | 68 | | 14 | 48 | | 15 | 39 | | 16 | 61 | | 17 | 48 | | 18 | 63 | | 19 | 21 | | 20 | 82 | | 21 | 53 | | 22 | 15 | | 23 | 83 | | 24 | 18 | | 25 | 21 | | 26 | 11 | | 27 | 3 |
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| 90.33% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 94 | | matches | | 0 | "been taught" | | 1 | "being poured" | | 2 | "been taught" | | 3 | "been told" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 223 | | matches | | 0 | "was keeping" | | 1 | "was listening" | | 2 | "was running" | | 3 | "were flattening" | | 4 | "was gaining" | | 5 | "were doing" | | 6 | "was running" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 95 | | ratio | 0.053 | | matches | | 0 | "Somewhere above the sodium haze there was a full moon, and she had reason now — she hated that she had reason — to care about that." | | 1 | "He raised one hand — not a wave." | | 2 | "Not machinery — voices." | | 3 | "No signal down there; she'd bet her pension on it." | | 4 | "She didn't know how she knew it, and that was the whole problem, that was the thing that had been eating her from the inside out for three years — the way she kept knowing things she hadn't been told." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 581 | | adjectiveStacks | 1 | | stackExamples | | 0 | "polite, complete, useless lies." |
| | adverbCount | 10 | | adverbRatio | 0.01721170395869191 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 14.73 | | std | 13.55 | | cv | 0.92 | | sampleLengths | | 0 | 34 | | 1 | 3 | | 2 | 12 | | 3 | 58 | | 4 | 3 | | 5 | 20 | | 6 | 28 | | 7 | 4 | | 8 | 4 | | 9 | 21 | | 10 | 9 | | 11 | 20 | | 12 | 2 | | 13 | 2 | | 14 | 32 | | 15 | 4 | | 16 | 4 | | 17 | 2 | | 18 | 27 | | 19 | 18 | | 20 | 13 | | 21 | 3 | | 22 | 27 | | 23 | 8 | | 24 | 3 | | 25 | 8 | | 26 | 42 | | 27 | 30 | | 28 | 19 | | 29 | 8 | | 30 | 4 | | 31 | 8 | | 32 | 2 | | 33 | 5 | | 34 | 15 | | 35 | 35 | | 36 | 8 | | 37 | 43 | | 38 | 1 | | 39 | 26 | | 40 | 4 | | 41 | 4 | | 42 | 7 | | 43 | 46 | | 44 | 27 | | 45 | 23 | | 46 | 8 | | 47 | 18 | | 48 | 8 | | 49 | 5 |
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| 63.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.47368421052631576 | | totalSentences | 95 | | uniqueOpeners | 45 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 84 | | matches | | 0 | "Somewhere above the sodium haze" | | 1 | "Then he went down the" | | 2 | "Then Herrera went after it," | | 3 | "Then she was inside, in" |
| | ratio | 0.048 | |
| 53.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 84 | | matches | | 0 | "She sat in the doorway" | | 1 | "He didn't look left." | | 2 | "He didn't look right." | | 3 | "He turned north and walked" | | 4 | "She knew Herrera the way" | | 5 | "She'd looked it up." | | 6 | "He crossed against the light" | | 7 | "Her watch strap had gone" | | 8 | "He broke into a run" | | 9 | "She'd been waiting for it" | | 10 | "She went after him and" | | 11 | "He was quick and he" | | 12 | "She ran the way she'd" | | 13 | "She didn't expect it to" | | 14 | "It never stopped them." | | 15 | "He lost half a stride." | | 16 | "She saw the satchel go" | | 17 | "He was running down the" | | 18 | "He didn't try to move" | | 19 | "He raised one hand —" |
| | ratio | 0.417 | |
| 90.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 84 | | matches | | 0 | "The rain had been falling" | | 1 | "THE RAVEN'S NEST." | | 2 | "The V flickered on a" | | 3 | "She sat in the doorway" | | 4 | "The door opened." | | 5 | "Tomás Herrera came out of" | | 6 | "He didn't look left." | | 7 | "He didn't look right." | | 8 | "He turned north and walked" | | 9 | "She knew Herrera the way" | | 10 | "Both times he had sat" | | 11 | "Patron saint of travellers." | | 12 | "She'd looked it up." | | 13 | "He crossed against the light" | | 14 | "Quinn dropped back, put a" | | 15 | "Her watch strap had gone" | | 16 | "He broke into a run" | | 17 | "That was fine." | | 18 | "She'd been waiting for it" | | 19 | "She went after him and" |
| | ratio | 0.738 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 10 | | matches | | 0 | "Twenty-nine, Seville-born, struck off the paramedic register two years ago for administering treatments that existed on no formulary in Europe." | | 1 | "He crossed against the light and a black cab laid on the horn and he didn't flinch, which meant he was listening for footsteps and not traffic." | | 2 | "He was running down the left and people were flattening against the right and she was gaining, actually gaining, close enough to hear his breath tearing." | | 3 | "Then she was inside, in the too-bright light, dripping on the floor of a carriage full of people who had decided very carefully to look at nothing." | | 4 | "He went left, through a gap in the tiling where a temporary hoarding said STATION IMPROVEMENT WORKS in cheerful blue, and the hoarding swung on a hinge somebody…" | | 5 | "A wooden staircase going down, disappearing after a dozen steps into a light that was not electric." | | 6 | "Dozens of them, layered and low, and under them a sound like glass beads being poured from hand to hand, and something that might have been an animal or might h…" | | 7 | "She didn't know how she knew it, and that was the whole problem, that was the thing that had been eating her from the inside out for three years — the way she k…" | | 8 | "Inside it, the button that wasn't a button: a flat oval of something ivory-pale, drilled once, incised with a mark like a bird's footprint." | | 9 | "Morris's, out of Morris's coat, and Morris had gone north on a full moon and come back on a trolley and nobody in eighteen years of decorated service had ever g…" |
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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 | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |