| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 18 | | tagDensity | 0.278 | | leniency | 0.556 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1167 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 95.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1167 | | totalAiIsms | 1 | | 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 | 79 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 79 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 92 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1178 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1087 | | uniqueNames | 14 | | maxNameDensity | 0.64 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 3 | | Detective | 1 | | Harlow | 1 | | Quinn | 7 | | Tomás | 1 | | Herrera | 4 | | High | 2 | | Street | 2 | | Kentish | 1 | | Town | 1 | | Islington | 1 | | Saint | 1 | | Christopher | 1 | | Morris | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Kentish" | | 4 | "Town" | | 5 | "Islington" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | 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 | 1178 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 92 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 29.45 | | std | 26.63 | | cv | 0.904 | | sampleLengths | | 0 | 22 | | 1 | 48 | | 2 | 78 | | 3 | 41 | | 4 | 9 | | 5 | 17 | | 6 | 16 | | 7 | 6 | | 8 | 4 | | 9 | 96 | | 10 | 40 | | 11 | 11 | | 12 | 7 | | 13 | 60 | | 14 | 52 | | 15 | 38 | | 16 | 11 | | 17 | 55 | | 18 | 10 | | 19 | 93 | | 20 | 3 | | 21 | 65 | | 22 | 16 | | 23 | 29 | | 24 | 16 | | 25 | 84 | | 26 | 22 | | 27 | 6 | | 28 | 3 | | 29 | 1 | | 30 | 4 | | 31 | 24 | | 32 | 26 | | 33 | 19 | | 34 | 3 | | 35 | 3 | | 36 | 48 | | 37 | 59 | | 38 | 12 | | 39 | 21 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 79 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 172 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 1 | | flaggedSentences | 9 | | totalSentences | 92 | | ratio | 0.098 | | matches | | 0 | "Three nights she'd tailed him — a basement in Kentish Town, a lockup in Islington, tonight Camden — and in all that time he had never once looked back." | | 1 | "Eighteen years on the job and she could still hold a sprint, but he was twenty-nine and had spent his working life hauling bodies down stairwells; he ran like a man who knew exactly how much body he had and what it could pay." | | 2 | "He cut through a gap in the hoarding into the dead market — shuttered stalls, awnings gulping rain, the iron horse standing in the dark with water running off its mane." | | 3 | "Herrera dug something pale from his jacket and rapped the steel with it — twice, a pause, three — and the door gave like it had been unlatched all along." | | 4 | "In eighteen years, everything she had ever chased had stopped in the end — leaned on a wall, dropped the bag, cried, bargained." | | 5 | "Decades of paint ghosted over a platform sign — WAY OUT, with an arrow pointing up at a city that had forgotten this hole existed." | | 6 | "Since then she had learned to eat the not-knowing — three meals a day, no relief between them." | | 7 | "Quinn unbuckled the watch — the leather strap worn to a shine, creased by another wrist before hers — and set it in the crone's palm." | | 8 | "The bones parted on their own, and heat rolled out — candle stubs burning in jam jars on trestles, sweet smoke, the clink of coin and glass, stalls climbing away into the dark of the old tunnel in both directions." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1082 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.024029574861367836 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0018484288354898336 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 92 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 92 | | mean | 12.8 | | std | 9.36 | | cv | 0.731 | | sampleLengths | | 0 | 22 | | 1 | 9 | | 2 | 25 | | 3 | 6 | | 4 | 8 | | 5 | 17 | | 6 | 29 | | 7 | 3 | | 8 | 10 | | 9 | 19 | | 10 | 10 | | 11 | 31 | | 12 | 9 | | 13 | 12 | | 14 | 5 | | 15 | 8 | | 16 | 8 | | 17 | 6 | | 18 | 4 | | 19 | 2 | | 20 | 31 | | 21 | 17 | | 22 | 2 | | 23 | 44 | | 24 | 7 | | 25 | 25 | | 26 | 8 | | 27 | 7 | | 28 | 4 | | 29 | 7 | | 30 | 31 | | 31 | 6 | | 32 | 23 | | 33 | 13 | | 34 | 9 | | 35 | 30 | | 36 | 6 | | 37 | 8 | | 38 | 24 | | 39 | 11 | | 40 | 2 | | 41 | 2 | | 42 | 10 | | 43 | 23 | | 44 | 12 | | 45 | 6 | | 46 | 10 | | 47 | 21 | | 48 | 25 | | 49 | 12 |
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| 66.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.44565217391304346 | | totalSentences | 92 | | uniqueOpeners | 41 | |
| 90.09% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 74 | | matches | | 0 | "Then he went in, and" | | 1 | "Somewhere in the crush, a" |
| | ratio | 0.027 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 74 | | matches | | 0 | "He came out now with" | | 1 | "She gave him half a" | | 2 | "He cut across the road" | | 3 | "She held up her warrant" | | 4 | "He gave her one look" | | 5 | "He rounded the corner by" | | 6 | "He took the lock footbridge" | | 7 | "Her voice tore on his" | | 8 | "He cut through a gap" | | 9 | "She'd logged off at eleven," | | 10 | "He looked back at her" | | 11 | "She slipped through before the" | | 12 | "She went down." | | 13 | "She rolled it under her" | | 14 | "She stepped out onto the" | | 15 | "It dropped into the apron" | | 16 | "She knocked one needle against" | | 17 | "She kept it in sight" |
| | ratio | 0.243 | |
| 88.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 74 | | matches | | 0 | "Rain came off the Camden" | | 1 | "Number 41 had swallowed Tomás" | | 2 | "He came out now with" | | 3 | "People afraid of arrest locked" | | 4 | "People afraid of something else" | | 5 | "She gave him half a" | | 6 | "Civilians looked back." | | 7 | "Civilians fussed with their phones" | | 8 | "Herrera walked like a man" | | 9 | "The screen lit his face" | | 10 | "He cut across the road" | | 11 | "She held up her warrant" | | 12 | "He gave her one look" | | 13 | "The Saint Christopher medallion jumped" | | 14 | "He rounded the corner by" | | 15 | "The canal bought her half" | | 16 | "He took the lock footbridge" | | 17 | "Her voice tore on his" | | 18 | "He cut through a gap" | | 19 | "She'd logged off at eleven," |
| | ratio | 0.743 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 3 | | matches | | 0 | "Down the High Street, past a kebab shop bleeding steam onto the pavement, past a hen party that shrieked as he took their table's edge in his palm and vaulted i…" | | 1 | "Eighteen years on the job and she could still hold a sprint, but he was twenty-nine and had spent his working life hauling bodies down stairwells; he ran like a…" | | 2 | "Warm air climbed past her, tasting of hot fat, smoke, old stone, and from far below came a sound like a hive that had moved into a cathedral: a hundred voices, …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |