| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.292 | | leniency | 0.583 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1255 | | 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) | |
| 92.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1255 | | 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 | 69 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 69 | | 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 | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1266 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 1 | | matches | | 0 | "Ten steps away, it snapped back to the arch." |
| |
| 77.34% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 757 | | uniqueNames | 7 | | maxNameDensity | 1.45 | | worstName | "Doyle" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Doyle" | | discoveredNames | | Quinn | 7 | | Doyle | 11 | | Crescent | 1 | | Dr | 1 | | Banerji | 2 | | Lena | 5 | | Morris | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Doyle" | | 2 | "Dr" | | 3 | "Banerji" | | 4 | "Lena" | | 5 | "Morris" |
| | places | | | globalScore | 0.773 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | 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 | 1266 | | 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 | 53 | | mean | 23.89 | | std | 18.1 | | cv | 0.758 | | sampleLengths | | 0 | 15 | | 1 | 67 | | 2 | 19 | | 3 | 4 | | 4 | 47 | | 5 | 8 | | 6 | 13 | | 7 | 50 | | 8 | 22 | | 9 | 1 | | 10 | 24 | | 11 | 48 | | 12 | 26 | | 13 | 4 | | 14 | 1 | | 15 | 53 | | 16 | 4 | | 17 | 10 | | 18 | 16 | | 19 | 13 | | 20 | 6 | | 21 | 11 | | 22 | 40 | | 23 | 9 | | 24 | 20 | | 25 | 3 | | 26 | 43 | | 27 | 14 | | 28 | 19 | | 29 | 15 | | 30 | 14 | | 31 | 45 | | 32 | 14 | | 33 | 6 | | 34 | 38 | | 35 | 58 | | 36 | 41 | | 37 | 8 | | 38 | 58 | | 39 | 20 | | 40 | 31 | | 41 | 19 | | 42 | 6 | | 43 | 50 | | 44 | 22 | | 45 | 11 | | 46 | 13 | | 47 | 64 | | 48 | 35 | | 49 | 34 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 69 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 120 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 101 | | ratio | 0.069 | | matches | | 0 | "Below, in the ticket hall, Doyle had planted his own torch upright on the floor, and its cone lit the ceiling tiles from beneath — the green of old bottle glass, flaked with ninety years of damp." | | 1 | "The dimming beam caught pools of candle wax at regular intervals along both platforms, and beneath the dust, rectangles scuffed clean — rows of them, in lanes, the length of the station." | | 2 | "She checked her watch out of habit — the leather strap had gone soft and dark with years of wear, and the mechanical hands ticked on, unbothered." | | 3 | "The dust on the steps held prints in plenty — dozens of sets, overlapping, all sizes." | | 4 | "They followed him along the trackbed — a dry canal of soot where the rails had been lifted decades before — to the tunnel mouth." | | 5 | "A disc hung from it — bone, thumb-width, polished by handling, carved with a mark: a keyhole inside a spiral." | | 6 | "The scuffed lanes between the pitches crossed and re-crossed — and where the lanes reached the centre of the platform, they bent." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 495 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.020202020202020204 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.00202020202020202 | |
| 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 | 12.53 | | std | 8.69 | | cv | 0.693 | | sampleLengths | | 0 | 15 | | 1 | 6 | | 2 | 8 | | 3 | 37 | | 4 | 7 | | 5 | 9 | | 6 | 13 | | 7 | 6 | | 8 | 4 | | 9 | 47 | | 10 | 8 | | 11 | 10 | | 12 | 3 | | 13 | 17 | | 14 | 2 | | 15 | 11 | | 16 | 11 | | 17 | 9 | | 18 | 22 | | 19 | 1 | | 20 | 24 | | 21 | 9 | | 22 | 32 | | 23 | 7 | | 24 | 5 | | 25 | 21 | | 26 | 4 | | 27 | 1 | | 28 | 21 | | 29 | 32 | | 30 | 4 | | 31 | 10 | | 32 | 16 | | 33 | 13 | | 34 | 6 | | 35 | 5 | | 36 | 6 | | 37 | 3 | | 38 | 27 | | 39 | 10 | | 40 | 9 | | 41 | 10 | | 42 | 10 | | 43 | 3 | | 44 | 8 | | 45 | 16 | | 46 | 2 | | 47 | 1 | | 48 | 16 | | 49 | 14 |
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| 97.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.6732673267326733 | | totalSentences | 101 | | uniqueOpeners | 68 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 62 | | matches | | 0 | "She tapped it against her" | | 1 | "He nodded down the passage" | | 2 | "She walked the nearest lane," | | 3 | "She checked her watch out" | | 4 | "She turned the thought over" | | 5 | "She walked to the stairs" | | 6 | "They followed him along the" | | 7 | "His notebook had carried a" | | 8 | "She'd memorised it without meaning" | | 9 | "She set the disc down" | | 10 | "She held it level." | | 11 | "She turned a full circle," | | 12 | "She walked it back to" | | 13 | "She held it over the" | | 14 | "It wanted the wall." | | 15 | "She raised the compass." |
| | ratio | 0.258 | |
| 40.65% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 62 | | matches | | 0 | "She tapped it against her" | | 1 | "The beam rallied, then shrank" | | 2 | "Hawley Crescent station had closed" | | 3 | "The dark down here had" | | 4 | "Doyle worked his gum, hands" | | 5 | "He nodded down the passage" | | 6 | "The body lay at the" | | 7 | "A wool coat that cost" | | 8 | "Dr Banerji crouched beside him" | | 9 | "Quinn circled the body at" | | 10 | "The dimming beam caught pools" | | 11 | "Chalk lines marked the corners" | | 12 | "Doyle spread his hands" | | 13 | "She walked the nearest lane," | | 14 | "A SOCO named Lena looked" | | 15 | "Quinn's torch guttered." | | 16 | "She checked her watch out" | | 17 | "Doyle saw the gesture and" | | 18 | "She turned the thought over" | | 19 | "She walked to the stairs" |
| | ratio | 0.839 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 0 | | effectiveRatio | 0 | |