| 66.67% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva said softly [softly]" | | 1 | "Quinn said finally [finally]" |
| | dialogueSentences | 23 | | tagDensity | 0.652 | | leniency | 1 | | rawRatio | 0.133 | | effectiveRatio | 0.133 | |
| 88.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1703 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | | | 3 | |
| | highlights | | 0 | "slightly" | | 1 | "deliberately" | | 2 | "softly" | | 3 | "carefully" |
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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) | |
| 58.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1703 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "porcelain" | | 1 | "echoing" | | 2 | "aligned" | | 3 | "etched" | | 4 | "trembled" | | 5 | "traced" | | 6 | "echoed" | | 7 | "perfect" | | 8 | "standard" | | 9 | "weight" | | 10 | "could feel" | | 11 | "familiar" | | 12 | "dancing" | | 13 | "charged" |
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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 | 131 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 131 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 139 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1702 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 76.06% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1420 | | uniqueNames | 11 | | maxNameDensity | 1.48 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 21 | | Eva | 10 | | Kowalski | 1 | | Morris | 3 | | British | 1 | | Museum | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Eva" | | 3 | "Kowalski" | | 4 | "Morris" | | 5 | "Market" |
| | places | (empty) | | globalScore | 0.761 | | windowScore | 0.833 | |
| 93.82% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 89 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like the air before a storm breaks" | | 1 | "as if fighting a drag" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1702 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 139 | | matches | | 0 | "buried that line" | | 1 | "lost that week" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 60.79 | | std | 32.87 | | cv | 0.541 | | sampleLengths | | 0 | 88 | | 1 | 81 | | 2 | 107 | | 3 | 13 | | 4 | 80 | | 5 | 20 | | 6 | 108 | | 7 | 4 | | 8 | 61 | | 9 | 84 | | 10 | 85 | | 11 | 71 | | 12 | 22 | | 13 | 97 | | 14 | 10 | | 15 | 66 | | 16 | 103 | | 17 | 6 | | 18 | 54 | | 19 | 23 | | 20 | 43 | | 21 | 89 | | 22 | 90 | | 23 | 34 | | 24 | 70 | | 25 | 61 | | 26 | 39 | | 27 | 93 |
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| 75.80% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 11 | | totalSentences | 131 | | matches | | 0 | "been pushed" | | 1 | "been shuttered" | | 2 | "was scarred" | | 3 | "been drawn" | | 4 | "was laid" | | 5 | "was scuffed" | | 6 | "was raised" | | 7 | "were filled" | | 8 | "been bricked" | | 9 | "been locked" | | 10 | "was hidden" |
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| 84.06% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 230 | | matches | | 0 | "was already fluttering" | | 1 | "was watching" | | 2 | "was still pointing" | | 3 | "was standing" |
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| 81.19% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 2 | | flaggedSentences | 3 | | totalSentences | 139 | | ratio | 0.022 | | matches | | 0 | "A nervous habit took over; Eva tucked a stray curl behind her left ear, her green eyes never leaving the floor." | | 1 | "The white feather she left on the tile; evidence of the ritual, but not of the killer." | | 2 | "And the geometry on the floor, the drag marks, the ledger, the locket—it all pointed to a network that had been operating in the blind spots of the city for longer than Quinn had been on the force." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1423 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.026704146170063246 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.009135628952916374 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 139 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 139 | | mean | 12.24 | | std | 8.84 | | cv | 0.722 | | sampleLengths | | 0 | 17 | | 1 | 18 | | 2 | 19 | | 3 | 10 | | 4 | 1 | | 5 | 11 | | 6 | 12 | | 7 | 18 | | 8 | 4 | | 9 | 12 | | 10 | 11 | | 11 | 2 | | 12 | 20 | | 13 | 3 | | 14 | 3 | | 15 | 8 | | 16 | 8 | | 17 | 13 | | 18 | 8 | | 19 | 3 | | 20 | 9 | | 21 | 21 | | 22 | 11 | | 23 | 8 | | 24 | 4 | | 25 | 2 | | 26 | 5 | | 27 | 15 | | 28 | 13 | | 29 | 24 | | 30 | 13 | | 31 | 21 | | 32 | 22 | | 33 | 8 | | 34 | 12 | | 35 | 14 | | 36 | 41 | | 37 | 7 | | 38 | 17 | | 39 | 13 | | 40 | 16 | | 41 | 4 | | 42 | 5 | | 43 | 28 | | 44 | 28 | | 45 | 3 | | 46 | 34 | | 47 | 3 | | 48 | 8 | | 49 | 17 |
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| 39.86% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.26811594202898553 | | totalSentences | 138 | | uniqueOpeners | 37 | |
| 57.47% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 116 | | matches | | 0 | "Just the rigid stillness of" | | 1 | "Just a uniform coating of" |
| | ratio | 0.017 | |
| 88.97% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 116 | | matches | | 0 | "It smelled of wet brick," | | 1 | "Her boots clicked against cracked" | | 2 | "She checked the worn leather" | | 3 | "She flashed her warrant card" | | 4 | "It sat in her gut" | | 5 | "They were too precise." | | 6 | "They terminated at clean, straight" | | 7 | "She adjusted her round glasses," | | 8 | "Her worn leather satchel sat" | | 9 | "She reached into the satchel," | | 10 | "She laid it on a" | | 11 | "She met Quinn's gaze" | | 12 | "She had buried that line" | | 13 | "She had spent eighteen years" | | 14 | "It felt like the air" | | 15 | "She rose, brushing dust from" | | 16 | "She checked the tiles again." | | 17 | "She flipped further, her breath" | | 18 | "She picked up the locket." | | 19 | "She had closed the satchel" |
| | ratio | 0.328 | |
| 50.52% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 95 | | totalSentences | 116 | | matches | | 0 | "The damp air of the" | | 1 | "It smelled of wet brick," | | 2 | "Her boots clicked against cracked" | | 3 | "She checked the worn leather" | | 4 | "The official time of discovery" | | 5 | "The tape across the service" | | 6 | "She flashed her warrant card" | | 7 | "The scene was wrong." | | 8 | "It sat in her gut" | | 9 | "The coroner’s preliminary note on" | | 10 | "A woman in her late" | | 11 | "Quinn crouched, her brown eyes" | | 12 | "The station had been shuttered" | | 13 | "A murder scene out here" | | 14 | "The floor around the body" | | 15 | "The responding officer had called" | | 16 | "Quinn stared at the edges" | | 17 | "They were too precise." | | 18 | "The burns didn’t fizzle out." | | 19 | "They terminated at clean, straight" |
| | ratio | 0.819 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 116 | | matches | (empty) | | ratio | 0 | |
| 75.89% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 6 | | matches | | 0 | "They terminated at clean, straight lines, as if something had been drawn and then erased." | | 1 | "She had buried that line of questioning three years ago, after DS Morris went silent on a case that ended with a crime scene full of impossible geometry and bod…" | | 2 | "It held its direction now, unblinking, pointing deeper into the dark, toward a section of the tunnel that had been bricked up for years." | | 3 | "Quinn could feel the pressure dropping in her ears, the familiar hollow ache in her temples that meant she was standing too close to something that wasn't suppo…" | | 4 | "And the geometry on the floor, the drag marks, the ledger, the locket—it all pointed to a network that had been operating in the blind spots of the city for lon…" | | 5 | "She looked at the bricked-up tunnel, at the faint drag marks leading into the dark, at the compass needle that had already begun to search for what was hidden." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 5 | | matches | | 0 | "Quinn replied, her voice flat" | | 1 | "Eva said, her tone calm, academic, edged with something sharper" | | 2 | "Quinn murmured, the words barely leaving her lips" | | 3 | "Eva said, her voice quieter now" | | 4 | "Quinn said, the realization settling over her like a cold weight" |
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| 63.04% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 2 | | fancyTags | | 0 | "Eva corrected (correct)" | | 1 | "Quinn murmured (murmur)" |
| | dialogueSentences | 23 | | tagDensity | 0.478 | | leniency | 0.957 | | rawRatio | 0.182 | | effectiveRatio | 0.174 | |