| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said again [again]" |
| | dialogueSentences | 82 | | tagDensity | 0.305 | | leniency | 0.61 | | rawRatio | 0.04 | | effectiveRatio | 0.024 | |
| 92.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2115 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "quickly" | | 1 | "carefully" | | 2 | "slowly" |
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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) | |
| 81.09% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2115 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "stomach" | | 1 | "etched" | | 2 | "silence" | | 3 | "shattered" | | 4 | "pulse" | | 5 | "magnetic" | | 6 | "mosaic" | | 7 | "chill" |
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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 | 175 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 175 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 232 | | 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 | 2114 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 30 | | unquotedAttributions | 1 | | matches | | 0 | "Not impossible, she told herself." |
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| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 64 | | wordCount | 1563 | | uniqueNames | 8 | | maxNameDensity | 1.73 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 27 | | London | 1 | | Camden | 1 | | Iqbal | 14 | | Eva | 18 | | Kowalski | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Iqbal" | | 3 | "Eva" | | 4 | "Kowalski" |
| | places | | | globalScore | 0.636 | | windowScore | 0.167 | |
| 83.04% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 112 | | glossingSentenceCount | 3 | | matches | | 0 | "appeared considered" | | 1 | "appeared solid" | | 2 | "seemed abruptly unarmed" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 0.946 | | wordCount | 2114 | | matches | | 0 | "not at the body, not at the compass, but at Quinn’s proximity to the wall" | | 1 | "not at the compass, but at Quinn’s proximity to the wall" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 232 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 133 | | mean | 15.89 | | std | 14.82 | | cv | 0.932 | | sampleLengths | | 0 | 24 | | 1 | 48 | | 2 | 25 | | 3 | 31 | | 4 | 37 | | 5 | 4 | | 6 | 15 | | 7 | 43 | | 8 | 19 | | 9 | 6 | | 10 | 5 | | 11 | 10 | | 12 | 52 | | 13 | 11 | | 14 | 25 | | 15 | 17 | | 16 | 57 | | 17 | 15 | | 18 | 28 | | 19 | 38 | | 20 | 4 | | 21 | 3 | | 22 | 39 | | 23 | 18 | | 24 | 3 | | 25 | 9 | | 26 | 11 | | 27 | 10 | | 28 | 55 | | 29 | 5 | | 30 | 3 | | 31 | 12 | | 32 | 34 | | 33 | 4 | | 34 | 19 | | 35 | 13 | | 36 | 3 | | 37 | 4 | | 38 | 42 | | 39 | 20 | | 40 | 15 | | 41 | 6 | | 42 | 4 | | 43 | 15 | | 44 | 33 | | 45 | 28 | | 46 | 13 | | 47 | 3 | | 48 | 6 | | 49 | 9 |
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| 91.23% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 175 | | matches | | 0 | "been rigged" | | 1 | "been buttoned" | | 2 | "was flattened" | | 3 | "been overturned" | | 4 | "been looped" | | 5 | "been restored" | | 6 | "was marked" |
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| 76.08% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 269 | | matches | | 0 | "was waking" | | 1 | "was listening" | | 2 | "was staring" | | 3 | "was not holding" | | 4 | "was holding" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 4 | | flaggedSentences | 1 | | totalSentences | 232 | | ratio | 0.004 | | matches | | 0 | "Remove the story and the facts became spare: a man killed or first laid down somewhere else; a room stripped and swept; a body placed where no carrier had walked; an object arranged in his hand; a needle fixed on a wall that should not have been drawing cold air." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1569 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 42 | | adverbRatio | 0.02676864244741874 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.008922880815806247 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 232 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 232 | | mean | 9.11 | | std | 6.87 | | cv | 0.754 | | sampleLengths | | 0 | 24 | | 1 | 10 | | 2 | 18 | | 3 | 8 | | 4 | 12 | | 5 | 10 | | 6 | 2 | | 7 | 13 | | 8 | 31 | | 9 | 4 | | 10 | 33 | | 11 | 4 | | 12 | 15 | | 13 | 20 | | 14 | 6 | | 15 | 17 | | 16 | 4 | | 17 | 15 | | 18 | 6 | | 19 | 5 | | 20 | 7 | | 21 | 3 | | 22 | 24 | | 23 | 28 | | 24 | 6 | | 25 | 5 | | 26 | 14 | | 27 | 5 | | 28 | 6 | | 29 | 17 | | 30 | 18 | | 31 | 12 | | 32 | 10 | | 33 | 11 | | 34 | 6 | | 35 | 8 | | 36 | 7 | | 37 | 9 | | 38 | 19 | | 39 | 5 | | 40 | 8 | | 41 | 16 | | 42 | 9 | | 43 | 4 | | 44 | 3 | | 45 | 22 | | 46 | 8 | | 47 | 9 | | 48 | 8 | | 49 | 10 |
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| 67.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.43103448275862066 | | totalSentences | 232 | | uniqueOpeners | 100 | |
| 46.62% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 143 | | matches | | 0 | "Even practiced criminals left the" | | 1 | "Barely, but enough." |
| | ratio | 0.014 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 143 | | matches | | 0 | "Their cables snaked over rails" | | 1 | "She was small, with curly" | | 2 | "He gestured at the folding" | | 3 | "It was not a stupid" | | 4 | "His grey coat had been" | | 5 | "His right hand rested palm-up" | | 6 | "Its face was crowded with" | | 7 | "She looked at the dead" | | 8 | "She indicated the bruise-dark discoloration" | | 9 | "His left ear was flattened" | | 10 | "He was listening now." | | 11 | "She stood and walked to" | | 12 | "She lowered herself again and" | | 13 | "She looked at the compass" | | 14 | "Its chain had been looped" | | 15 | "It might have been a" | | 16 | "It might have been a" | | 17 | "It showed a bone-white disc" | | 18 | "she said again, more quietly" | | 19 | "He turned it once more." |
| | ratio | 0.21 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 143 | | matches | | 0 | "Their cables snaked over rails" | | 1 | "Quinn checked the worn leather" | | 2 | "DS Iqbal waited beside the" | | 3 | "She was small, with curly" | | 4 | "A worn leather satchel rested" | | 5 | "Quinn looked past him toward" | | 6 | "He gestured at the folding" | | 7 | "It was not a stupid" | | 8 | "That was what annoyed her." | | 9 | "The market explanation accounted for" | | 10 | "The body supplied the violence." | | 11 | "An empty station did the" | | 12 | "Quinn walked the blue sterile" | | 13 | "The dead man lay on" | | 14 | "His grey coat had been" | | 15 | "A narrow slit marked his" | | 16 | "Blood had darkened the fabric" | | 17 | "His right hand rested palm-up" | | 18 | "Verdigris had settled into the" | | 19 | "Its face was crowded with" |
| | ratio | 0.65 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 143 | | matches | | 0 | "By the time Detective Harlow" | | 1 | "Therefore either Eva’s story was" | | 2 | "As if evidence became less" |
| | ratio | 0.021 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 3 | | matches | | 0 | "DS Iqbal waited beside the old ticket barrier with a paper cup of coffee and the expression of a man who had already decided which parts of the morning were inc…" | | 1 | "Iqbal gave a slight nod, as if one small piece of normality had been restored." | | 2 | "Remove the story and the facts became spare: a man killed or first laid down somewhere else; a room stripped and swept; a body placed where no carrier had walke…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 23 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 82 | | tagDensity | 0.28 | | leniency | 0.561 | | rawRatio | 0 | | effectiveRatio | 0 | |