| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 71 | | tagDensity | 0.141 | | leniency | 0.282 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1873 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "very" | | 2 | "softly" |
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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) | |
| 65.30% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1873 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "warmth" | | 1 | "chill" | | 2 | "measured" | | 3 | "weight" | | 4 | "flickered" | | 5 | "whisper" | | 6 | "velvet" | | 7 | "charm" | | 8 | "glint" | | 9 | "etched" |
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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 | 156 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 156 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 216 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1872 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 73.69% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1376 | | uniqueNames | 10 | | maxNameDensity | 1.53 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 21 | | Tube | 1 | | Camden | 1 | | Sergeant | 1 | | Vale | 16 | | Metropolitan | 1 | | Police | 1 | | Lyle | 4 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Vale" | | 4 | "Lyle" | | 5 | "Morris" |
| | places | | | globalScore | 0.737 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 98 | | 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 | 1872 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 216 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 110 | | mean | 17.02 | | std | 17.28 | | cv | 1.016 | | sampleLengths | | 0 | 14 | | 1 | 66 | | 2 | 22 | | 3 | 8 | | 4 | 4 | | 5 | 58 | | 6 | 50 | | 7 | 54 | | 8 | 32 | | 9 | 3 | | 10 | 35 | | 11 | 2 | | 12 | 6 | | 13 | 39 | | 14 | 3 | | 15 | 16 | | 16 | 2 | | 17 | 56 | | 18 | 35 | | 19 | 8 | | 20 | 17 | | 21 | 2 | | 22 | 9 | | 23 | 45 | | 24 | 3 | | 25 | 29 | | 26 | 4 | | 27 | 5 | | 28 | 21 | | 29 | 8 | | 30 | 7 | | 31 | 42 | | 32 | 6 | | 33 | 4 | | 34 | 5 | | 35 | 6 | | 36 | 4 | | 37 | 2 | | 38 | 7 | | 39 | 57 | | 40 | 15 | | 41 | 14 | | 42 | 4 | | 43 | 9 | | 44 | 28 | | 45 | 26 | | 46 | 7 | | 47 | 2 | | 48 | 4 | | 49 | 4 |
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| 76.02% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 13 | | totalSentences | 156 | | matches | | 0 | "been sealed" | | 1 | "been touched" | | 2 | "been moved" | | 3 | "been torn" | | 4 | "been fixed" | | 5 | "been pried" | | 6 | "been brushed" | | 7 | "was lined" | | 8 | "been made" | | 9 | "been opened" | | 10 | "were curled" | | 11 | "been made" | | 12 | "been made" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 215 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 216 | | ratio | 0.009 | | matches | | 0 | "The station smelled of wet stone, dust, and something sharp beneath it—like coins held too long in a closed fist." | | 1 | "Under it, barely visible through the clear plastic, a second set of footprints crossed the tile—small, narrow impressions that had never touched dust." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1380 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.025362318840579712 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.005072463768115942 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 216 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 216 | | mean | 8.67 | | std | 6.46 | | cv | 0.745 | | sampleLengths | | 0 | 14 | | 1 | 10 | | 2 | 25 | | 3 | 10 | | 4 | 21 | | 5 | 9 | | 6 | 2 | | 7 | 11 | | 8 | 8 | | 9 | 4 | | 10 | 5 | | 11 | 8 | | 12 | 20 | | 13 | 9 | | 14 | 4 | | 15 | 4 | | 16 | 8 | | 17 | 20 | | 18 | 19 | | 19 | 11 | | 20 | 10 | | 21 | 13 | | 22 | 13 | | 23 | 8 | | 24 | 10 | | 25 | 6 | | 26 | 1 | | 27 | 1 | | 28 | 7 | | 29 | 17 | | 30 | 3 | | 31 | 5 | | 32 | 30 | | 33 | 2 | | 34 | 6 | | 35 | 8 | | 36 | 23 | | 37 | 2 | | 38 | 2 | | 39 | 4 | | 40 | 3 | | 41 | 16 | | 42 | 2 | | 43 | 16 | | 44 | 40 | | 45 | 4 | | 46 | 21 | | 47 | 5 | | 48 | 5 | | 49 | 8 |
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| 55.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3611111111111111 | | totalSentences | 216 | | uniqueOpeners | 78 | |
| 25.06% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 133 | | matches | | 0 | "Then the barrier arm lifted" |
| | ratio | 0.008 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 133 | | matches | | 0 | "She paused at the top" | | 1 | "Her worn watch pressed against" | | 2 | "She kept her eyes moving:" | | 3 | "His coat was expensive, though" | | 4 | "His face had fixed in" | | 5 | "They began near the body," | | 6 | "She moved to the ticket" | | 7 | "Their metal arms had been" | | 8 | "She touched the nearest bar" | | 9 | "She ran her gaze along" | | 10 | "Its cover hung at an" | | 11 | "It had been brushed aside" | | 12 | "His boot left a damp" | | 13 | "She leaned over the first" | | 14 | "It sat across the blood" | | 15 | "She followed their faint trail" | | 16 | "It began almost beneath the" | | 17 | "Its edges were sharp, the" | | 18 | "She crouched again and examined" | | 19 | "His trousers were dry from" |
| | ratio | 0.218 | |
| 69.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 104 | | totalSentences | 133 | | matches | | 0 | "The station had been sealed" | | 1 | "Detective Harlow Quinn noticed that" | | 2 | "She paused at the top" | | 3 | "A line of yellow police" | | 4 | "The warmth came through the" | | 5 | "A living warmth, not the" | | 6 | "Quinn descended with measured care." | | 7 | "Her worn watch pressed against" | | 8 | "She kept her eyes moving:" | | 9 | "The station smelled of wet" | | 10 | "The old platform lay open" | | 11 | "The crime scene occupied the" | | 12 | "A man lay on his" | | 13 | "His coat was expensive, though" | | 14 | "Blood had soaked the front" | | 15 | "A paper cup stood upright" | | 16 | "Quinn looked at the body" | | 17 | "His face had fixed in" | | 18 | "Quinn nodded once and crouched" | | 19 | "The blood had spread in" |
| | ratio | 0.782 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 133 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 3 | | matches | | 0 | "Beyond it, her colleagues moved through the stale dark beneath portable lamps, their shadows jumping over old advertisements and flaking tiles." | | 1 | "The warmth beneath her palm, the clean arc in the dust, the blood thread disappearing under the metal, the prints that began beside the body and grew weaker wit…" | | 2 | "Under it, barely visible through the clear plastic, a second set of footprints crossed the tile—small, narrow impressions that had never touched dust." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 71 | | tagDensity | 0.141 | | leniency | 0.282 | | rawRatio | 0.1 | | effectiveRatio | 0.028 | |