| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "PC Odell peeled away [away]" |
| | dialogueSentences | 29 | | tagDensity | 0.276 | | leniency | 0.552 | | rawRatio | 0.125 | | effectiveRatio | 0.069 | |
| 95.77% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1183 | | 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) | |
| 78.87% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1183 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "footsteps" | | 1 | "flicked" | | 2 | "stomach" | | 3 | "charged" |
| |
| 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 | 75 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 75 | | 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 | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1198 | | ratio | 0 | | matches | (empty) | |
| 93.75% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 1 | | matches | | 0 | "Graffiti, she told herself." |
| |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 922 | | uniqueNames | 11 | | maxNameDensity | 1.52 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Eva" | | discoveredNames | | Camden | 1 | | Quinn | 14 | | Blitz | 1 | | Morris | 3 | | Odell | 4 | | Tiny | 1 | | Kowalski | 3 | | Spitalfields | 1 | | Eva | 9 | | Tube | 1 | | Whitechapel | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Odell" | | 3 | "Kowalski" | | 4 | "Eva" |
| | places | | 0 | "Spitalfields" | | 1 | "Whitechapel" |
| | globalScore | 0.741 | | windowScore | 0.667 | |
| 2.94% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | glossingSentenceCount | 3 | | matches | | 0 | "quite name — not decay, exactly" | | 1 | "looked like chalk and red ochre" | | 2 | "not quite runes, not quite letters" | | 3 | "not quite letters" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.835 | | wordCount | 1198 | | matches | | 0 | "No second set of footprints but" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 32.38 | | std | 24.05 | | cv | 0.743 | | sampleLengths | | 0 | 41 | | 1 | 74 | | 2 | 36 | | 3 | 9 | | 4 | 4 | | 5 | 31 | | 6 | 48 | | 7 | 69 | | 8 | 3 | | 9 | 38 | | 10 | 2 | | 11 | 4 | | 12 | 66 | | 13 | 6 | | 14 | 14 | | 15 | 47 | | 16 | 2 | | 17 | 14 | | 18 | 76 | | 19 | 9 | | 20 | 16 | | 21 | 52 | | 22 | 50 | | 23 | 3 | | 24 | 4 | | 25 | 2 | | 26 | 36 | | 27 | 35 | | 28 | 63 | | 29 | 49 | | 30 | 44 | | 31 | 33 | | 32 | 64 | | 33 | 67 | | 34 | 11 | | 35 | 50 | | 36 | 26 |
| |
| 77.19% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 75 | | matches | | 0 | "were cracked" | | 1 | "been poured" | | 2 | "been scored" | | 3 | "been painted" | | 4 | "were meant" | | 5 | "been looped" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 146 | | matches | | 0 | "was already tucking" | | 1 | "was still tucking" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 95 | | ratio | 0.074 | | matches | | 0 | "The stairs down into the old Camden station smelled of damp brick and something else Quinn couldn't quite name — not decay, exactly." | | 1 | "The tiles here were cracked in long diagonals, and someone — not recently — had painted sigils on them in what looked like chalk and red ochre." | | 2 | "His eyes were open, and they were entirely white — not rolled back, Quinn saw as she crouched beside him." | | 3 | "Her red hair had escaped its tie on one side, and she was already tucking it behind her left ear in that small, nervous gesture Quinn had noted twice before — once across an interview table, once at a crime scene in Spitalfields where Kowalski had no earthly reason to be." | | 4 | "If they had been theatrical, Quinn thought, they would have been painted for effect — bold, large, visible from the stairs." | | 5 | "Five — and here Quinn's stomach did the thing it had done once before, three years ago, in a basement in Whitechapel where Morris had walked in and never walked out — the air." | | 6 | "She smiled — a small, practiced, apologetic smile — and Quinn marked that too, and filed it, and waited." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 606 | | adjectiveStacks | 1 | | stackExamples | | 0 | "hard pressed against her" |
| | adverbCount | 24 | | adverbRatio | 0.039603960396039604 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.00825082508250825 | |
| 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 | 12.61 | | std | 10.42 | | cv | 0.827 | | sampleLengths | | 0 | 23 | | 1 | 2 | | 2 | 16 | | 3 | 38 | | 4 | 9 | | 5 | 14 | | 6 | 7 | | 7 | 6 | | 8 | 26 | | 9 | 10 | | 10 | 9 | | 11 | 4 | | 12 | 16 | | 13 | 11 | | 14 | 4 | | 15 | 6 | | 16 | 27 | | 17 | 6 | | 18 | 4 | | 19 | 5 | | 20 | 31 | | 21 | 3 | | 22 | 2 | | 23 | 20 | | 24 | 4 | | 25 | 9 | | 26 | 3 | | 27 | 7 | | 28 | 31 | | 29 | 2 | | 30 | 4 | | 31 | 13 | | 32 | 16 | | 33 | 14 | | 34 | 23 | | 35 | 6 | | 36 | 2 | | 37 | 12 | | 38 | 17 | | 39 | 14 | | 40 | 16 | | 41 | 2 | | 42 | 12 | | 43 | 2 | | 44 | 25 | | 45 | 51 | | 46 | 9 | | 47 | 6 | | 48 | 10 | | 49 | 18 |
| |
| 79.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.5263157894736842 | | totalSentences | 95 | | uniqueOpeners | 50 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 65 | | matches | | 0 | "She descended past the peeling" | | 1 | "Her boots struck the concrete" | | 2 | "His eyes were open, and" | | 3 | "She parted the coat and" | | 4 | "She held the bone up" | | 5 | "She set it aside on" | | 6 | "Her red hair had escaped" | | 7 | "She let Eva's interpretation sit" | | 8 | "They weren't meant to frighten" | | 9 | "They were meant to work." | | 10 | "She stepped back toward the" | | 11 | "She kept her voice level." | | 12 | "She rose to her full" | | 13 | "She smiled — a small," |
| | ratio | 0.215 | |
| 98.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 65 | | matches | | 0 | "The stairs down into the" | | 1 | "Something that made the small" | | 2 | "She descended past the peeling" | | 3 | "Her boots struck the concrete" | | 4 | "DS Morris used to laugh" | | 5 | "Morris wasn't here to laugh" | | 6 | "PC Odell peeled away from" | | 7 | "Quinn pulled on a pair" | | 8 | "The leather strap of her" | | 9 | "Odell led her along the" | | 10 | "The tiles here were cracked" | | 11 | "Quinn catalogued the markings without" | | 12 | "Graffiti, she told herself." | | 13 | "Some idiot's idea of atmosphere." | | 14 | "The body lay at the" | | 15 | "His eyes were open, and" | | 16 | "Quinn lifted the edge of" | | 17 | "The lining was cold, and" | | 18 | "She parted the coat and" | | 19 | "She held the bone up" |
| | ratio | 0.723 | |
| 76.92% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 65 | | matches | | 0 | "If they had been theatrical," |
| | ratio | 0.015 | |
| 56.28% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 4 | | matches | | 0 | "Something that made the small hairs at the nape of her neck lift beneath her collar." | | 1 | "She descended past the peeling tile, past a painted arrow pointing to a platform that hadn't served a train since the Blitz, and ducked under a strand of police…" | | 2 | "The body lay at the far end, a man in his thirties, suit trousers and a dark woolen coat fanned out behind him as if he'd been mid-stride when he'd fallen." | | 3 | "She let Eva's interpretation sit in the air, polite and reasonable and entirely wrong, and began to list the things that didn't belong in it." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.069 | | leniency | 0.138 | | rawRatio | 0 | | effectiveRatio | 0 | |