| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 113 | | tagDensity | 0.124 | | leniency | 0.248 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2520 | | totalAiIsmAdverbs | 5 | | found | | 0 | | | 1 | | adverb | "reluctantly" | | count | 1 |
| | 2 | | | 3 | | | 4 | |
| | highlights | | 0 | "sharply" | | 1 | "reluctantly" | | 2 | "precisely" | | 3 | "slightly" | | 4 | "gently" |
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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) | |
| 66.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2520 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "weight" | | 1 | "velvet" | | 2 | "predictable" | | 3 | "familiar" | | 4 | "flicked" | | 5 | "silence" | | 6 | "etched" | | 7 | "trembled" | | 8 | "quivered" | | 9 | "wavered" | | 10 | "pulse" | | 11 | "aligned" | | 12 | "warmth" |
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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 | 264 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 264 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 363 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2519 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 1 | | matches | | 0 | "Teeth Bought, No Questions." |
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| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 106 | | wordCount | 1999 | | uniqueNames | 15 | | maxNameDensity | 2.75 | | worstName | "Quinn" | | maxWindowNameDensity | 6 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 55 | | London | 1 | | Kowalski | 3 | | British | 1 | | Museum | 1 | | Shah | 13 | | Eva | 22 | | Luck | 1 | | Hauntings | 1 | | Bought | 1 | | Questions | 1 | | Morris | 3 | | July | 1 | | Don | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Museum" | | 4 | "Shah" | | 5 | "Eva" | | 6 | "Morris" |
| | places | | | globalScore | 0.124 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 146 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed printed rather than cut" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.397 | | wordCount | 2519 | | matches | | 0 | "not at the corpse now, but through him" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 363 | | matches | | 0 | "showed that someone" | | 1 | "saw that its" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 219 | | mean | 11.5 | | std | 13.51 | | cv | 1.174 | | sampleLengths | | 0 | 32 | | 1 | 10 | | 2 | 10 | | 3 | 92 | | 4 | 16 | | 5 | 3 | | 6 | 13 | | 7 | 42 | | 8 | 4 | | 9 | 54 | | 10 | 4 | | 11 | 6 | | 12 | 32 | | 13 | 12 | | 14 | 58 | | 15 | 4 | | 16 | 5 | | 17 | 13 | | 18 | 35 | | 19 | 4 | | 20 | 8 | | 21 | 1 | | 22 | 7 | | 23 | 4 | | 24 | 7 | | 25 | 3 | | 26 | 9 | | 27 | 18 | | 28 | 3 | | 29 | 24 | | 30 | 2 | | 31 | 16 | | 32 | 4 | | 33 | 1 | | 34 | 42 | | 35 | 1 | | 36 | 11 | | 37 | 3 | | 38 | 2 | | 39 | 2 | | 40 | 2 | | 41 | 7 | | 42 | 6 | | 43 | 1 | | 44 | 12 | | 45 | 48 | | 46 | 5 | | 47 | 5 | | 48 | 7 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 264 | | matches | | 0 | "was studded" | | 1 | "was carved" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 328 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 363 | | ratio | 0.008 | | matches | | 0 | "Only a black smear on the wall and Morris’s final note in handwriting that deteriorated into a jagged line: Don’t let it see—" | | 1 | "Eva’s was carved with a spiral; the dead man’s showed a symbol like a closed eye." | | 2 | "It pointed not at the corpse now, but through him—toward the stained tiles beneath the WAY OUT sign." |
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| 82.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2011 | | adjectiveStacks | 3 | | stackExamples | | 0 | "North lay over her" | | 1 | "same grey-white colour" | | 2 | "under gas-blue flames," |
| | adverbCount | 62 | | adverbRatio | 0.030830432620586774 | | lyAdverbCount | 24 | | lyAdverbRatio | 0.011934361014420686 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 363 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 363 | | mean | 6.94 | | std | 5.4 | | cv | 0.778 | | sampleLengths | | 0 | 32 | | 1 | 10 | | 2 | 10 | | 3 | 13 | | 4 | 22 | | 5 | 11 | | 6 | 6 | | 7 | 7 | | 8 | 11 | | 9 | 22 | | 10 | 11 | | 11 | 5 | | 12 | 3 | | 13 | 7 | | 14 | 6 | | 15 | 13 | | 16 | 8 | | 17 | 9 | | 18 | 12 | | 19 | 4 | | 20 | 5 | | 21 | 3 | | 22 | 25 | | 23 | 2 | | 24 | 3 | | 25 | 3 | | 26 | 13 | | 27 | 4 | | 28 | 6 | | 29 | 1 | | 30 | 16 | | 31 | 15 | | 32 | 12 | | 33 | 15 | | 34 | 19 | | 35 | 8 | | 36 | 16 | | 37 | 4 | | 38 | 5 | | 39 | 2 | | 40 | 2 | | 41 | 9 | | 42 | 10 | | 43 | 20 | | 44 | 5 | | 45 | 4 | | 46 | 3 | | 47 | 5 | | 48 | 1 | | 49 | 7 |
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| 58.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.3774104683195592 | | totalSentences | 363 | | uniqueOpeners | 137 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 218 | | matches | | 0 | "Repeatedly adjacent to people Quinn" | | 1 | "More than clean: soft, pink," | | 2 | "Instead, she held Eva’s gaze." | | 3 | "Only a black smear on" | | 4 | "Directly above the body, an" | | 5 | "More tellingly, dust coated the" | | 6 | "Only the eyes moved." | | 7 | "Then the opening narrowed." |
| | ratio | 0.037 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 218 | | matches | | 0 | "She knew the occupation, too." | | 1 | "His boots were dry despite" | | 2 | "His eyes were open." | | 3 | "They had turned entirely black." | | 4 | "She had once attended a" | | 5 | "Her knees protested." | | 6 | "It came too sharply." | | 7 | "His right sleeve lay smooth" | | 8 | "She sounded sorry." | | 9 | "She did not look at" | | 10 | "She had found no vent," | | 11 | "She shut the memory down." | | 12 | "She crouched beside the waistcoat" | | 13 | "It was small and unexpectedly" | | 14 | "It did not point north." | | 15 | "It pointed at the dead" | | 16 | "She walked toward the tunnel." | | 17 | "She examined the tiles around" | | 18 | "She rose and approached the" | | 19 | "It formed long downward streaks," |
| | ratio | 0.142 | |
| 86.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 163 | | totalSentences | 218 | | matches | | 0 | "The dead man lay between" | | 1 | "Detective Harlow Quinn stopped three" | | 2 | "Canvas awnings sagged from iron" | | 3 | "A bitter smell of burnt" | | 4 | "Quinn glanced at the worn" | | 5 | "The constable behind her shifted" | | 6 | "The woman in question sat" | | 7 | "A worn leather satchel rested" | | 8 | "Quinn knew the name." | | 9 | "She knew the occupation, too." | | 10 | "Eva Kowalski, twenty-six." | | 11 | "Quinn turned back to the" | | 12 | "Shah crouched beside the dead" | | 13 | "Quinn approached with military care," | | 14 | "The man wore a bottle-green" | | 15 | "The clothes looked theatrical until" | | 16 | "His boots were dry despite" | | 17 | "Rings crowded seven fingers, though" | | 18 | "His eyes were open." | | 19 | "They had turned entirely black." |
| | ratio | 0.748 | |
| 68.81% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 218 | | matches | | 0 | "If he had crawled, dust" | | 1 | "Either could explain Kowalski’s presence." | | 2 | "Now she saw that its" |
| | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 77 | | technicalSentenceCount | 2 | | matches | | 0 | "The dead man lay between a shuttered apothecary stall and the edge of the northbound platform, his right hand stretched toward the tracks as if the last train h…" | | 1 | "Research assistant at the British Museum’s restricted archives, which was a grand institutional phrase for rooms that officially held water-damaged inventories …" |
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| 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 | 12 | | fancyCount | 1 | | fancyTags | | 0 | "Eva whispered (whisper)" |
| | dialogueSentences | 113 | | tagDensity | 0.106 | | leniency | 0.212 | | rawRatio | 0.083 | | effectiveRatio | 0.018 | |