| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 1 | | adverbTags | | 0 | "A bell rang twice [twice]" |
| | dialogueSentences | 14 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0.167 | | effectiveRatio | 0.143 | |
| 92.52% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1337 | | 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) | |
| 92.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1337 | | 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 | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 101 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | 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 | 0 | | markdownWords | 0 | | totalWords | 1337 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 84.64% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1224 | | uniqueNames | 11 | | maxNameDensity | 1.31 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 16 | | Bayham | 1 | | Place | 1 | | Argyle | 1 | | Street | 1 | | Polite | 1 | | Neville | 1 | | Morris | 4 | | Deptford | 1 | | Tube | 1 | | Somebody | 4 |
| | persons | | 0 | "Quinn" | | 1 | "Neville" | | 2 | "Morris" |
| | places | | 0 | "Bayham" | | 1 | "Place" | | 2 | "Argyle" | | 3 | "Street" | | 4 | "Deptford" | | 5 | "Somebody" |
| | globalScore | 0.846 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed genuinely interested" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1337 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 110 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 27.85 | | std | 25.4 | | cv | 0.912 | | sampleLengths | | 0 | 36 | | 1 | 6 | | 2 | 6 | | 3 | 52 | | 4 | 18 | | 5 | 29 | | 6 | 7 | | 7 | 5 | | 8 | 81 | | 9 | 5 | | 10 | 42 | | 11 | 8 | | 12 | 24 | | 13 | 12 | | 14 | 4 | | 15 | 37 | | 16 | 80 | | 17 | 17 | | 18 | 29 | | 19 | 6 | | 20 | 16 | | 21 | 2 | | 22 | 18 | | 23 | 8 | | 24 | 88 | | 25 | 18 | | 26 | 8 | | 27 | 53 | | 28 | 17 | | 29 | 1 | | 30 | 13 | | 31 | 67 | | 32 | 44 | | 33 | 8 | | 34 | 41 | | 35 | 11 | | 36 | 66 | | 37 | 25 | | 38 | 26 | | 39 | 12 | | 40 | 103 | | 41 | 23 | | 42 | 60 | | 43 | 6 | | 44 | 53 | | 45 | 6 | | 46 | 9 | | 47 | 31 |
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| 94.84% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 101 | | matches | | 0 | "been was" | | 1 | "being tuned" | | 2 | "been floored" |
| |
| 48.48% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 220 | | matches | | 0 | "were shaking" | | 1 | "was selling" | | 2 | "was braiding" | | 3 | "was looking" | | 4 | "was speaking" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 110 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 586 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.032423208191126277 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0034129692832764505 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 12.15 | | std | 11.44 | | cv | 0.941 | | sampleLengths | | 0 | 36 | | 1 | 6 | | 2 | 3 | | 3 | 3 | | 4 | 13 | | 5 | 17 | | 6 | 9 | | 7 | 9 | | 8 | 4 | | 9 | 18 | | 10 | 4 | | 11 | 2 | | 12 | 23 | | 13 | 2 | | 14 | 5 | | 15 | 5 | | 16 | 32 | | 17 | 6 | | 18 | 2 | | 19 | 41 | | 20 | 5 | | 21 | 3 | | 22 | 12 | | 23 | 27 | | 24 | 8 | | 25 | 2 | | 26 | 12 | | 27 | 10 | | 28 | 9 | | 29 | 1 | | 30 | 2 | | 31 | 4 | | 32 | 28 | | 33 | 5 | | 34 | 4 | | 35 | 12 | | 36 | 26 | | 37 | 4 | | 38 | 38 | | 39 | 5 | | 40 | 12 | | 41 | 2 | | 42 | 27 | | 43 | 6 | | 44 | 9 | | 45 | 7 | | 46 | 2 | | 47 | 7 | | 48 | 11 | | 49 | 5 |
| |
| 60.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.43636363636363634 | | totalSentences | 110 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 83 | | matches | | 0 | "Then the scaffolding, hand over" | | 1 | "Then he'd walked out of" | | 2 | "Then he went down the" |
| | ratio | 0.036 | |
| 80.24% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 83 | | matches | | 0 | "He didn't stop." | | 1 | "They never did." | | 2 | "She'd first seen him ninety" | | 3 | "He'd looked directly into the" | | 4 | "She went up the scaffolding." | | 5 | "Her shoulder screamed." | | 6 | "Her fingers slipped on the" | | 7 | "She hauled herself onto the" | | 8 | "He dropped off the far" | | 9 | "She came up running." | | 10 | "They ran past the shuttered" | | 11 | "He went into the tunnel." | | 12 | "She had her baton out" | | 13 | "He tilted his head" | | 14 | "She'd stood in that basement" | | 15 | "He smiled, and the wall" | | 16 | "He stepped through." | | 17 | "He looked back at her," | | 18 | "It said: radio it in." | | 19 | "It said: you have no" |
| | ratio | 0.349 | |
| 80.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 83 | | matches | | 0 | "The suspect went left at" | | 1 | "He didn't stop." | | 2 | "They never did." | | 3 | "Rain came down in sheets" | | 4 | "Quinn's boots hammered wet pavement," | | 5 | "Quinn used her legs." | | 6 | "Water ran off her chin." | | 7 | "She'd first seen him ninety" | | 8 | "He'd looked directly into the" | | 9 | "She went up the scaffolding." | | 10 | "Her shoulder screamed." | | 11 | "Her fingers slipped on the" | | 12 | "She hauled herself onto the" | | 13 | "The eyes didn't catch the" | | 14 | "He dropped off the far" | | 15 | "She came up running." | | 16 | "Camden at half two in" | | 17 | "They ran past the shuttered" | | 18 | "The rain kept coming." | | 19 | "The canal appeared on her" |
| | ratio | 0.759 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 83 | | matches | (empty) | | ratio | 0 | |
| 34.16% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 7 | | matches | | 0 | "The suspect went left at the kebab shop, which was a mistake, because Quinn had grown up three streets from here and knew that Bayham Place dead-ended in a buil…" | | 1 | "Then the scaffolding, hand over hand, two storeys in about four seconds, moving like something that had shed the usual arrangement of joints." | | 2 | "She'd first seen him ninety minutes earlier on the CCTV feed from the Argyle Street lockups, standing over a body that was missing most of its blood and all of …" | | 3 | "Then he'd walked out of frame and hadn't reappeared on any of the eleven cameras between there and the main road, which was impossible, and which was exactly th…" | | 4 | "They ran past the shuttered market stalls, past a boarded pub with fairy lights still blinking behind the plywood, past a fox that didn't bother moving." | | 5 | "It said: whatever went through that wall is not a suspect, it is a category of thing that has no PACE code." | | 6 | "Somebody who wore a leather apron and had one hand resting on a cleaver the length of Quinn's forearm." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.214 | | leniency | 0.429 | | rawRatio | 0 | | effectiveRatio | 0 | |