| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1779 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 63.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1779 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "etched" | | 1 | "scanned" | | 2 | "glinting" | | 3 | "lilt" | | 4 | "quivered" | | 5 | "magnetic" | | 6 | "tracing" | | 7 | "flickered" | | 8 | "traced" | | 9 | "silence" | | 10 | "implication" |
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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 | 88 | | matches | (empty) | |
| 77.92% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 88 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 106 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 8 | | totalWords | 1768 | | ratio | 0.005 | | matches | | 0 | "To find what is hidden, follow the wound." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1059 | | uniqueNames | 12 | | maxNameDensity | 1.98 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 2 | | Quinn | 21 | | Town | 1 | | Blitz | 1 | | Veil | 1 | | Market | 1 | | Mornington | 1 | | Crescent | 1 | | Oxford | 1 | | Eva | 15 | | Morris | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Eva" | | 3 | "Morris" |
| | places | | 0 | "Town" | | 1 | "Mornington" | | 2 | "Crescent" | | 3 | "Oxford" |
| | globalScore | 0.508 | | windowScore | 0.5 | |
| 27.05% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 3 | | matches | | 0 | "arch that seemed to swallow the light" | | 1 | "looked like an apothecary’s stall, glass" | | 2 | "as if passing through a lens of warped air" |
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| 86.88% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.131 | | wordCount | 1768 | | matches | | 0 | "not north but directly at the victim’s chest" | | 1 | "Not to keep something out, but to direct it toward a specific target" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 106 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 49.11 | | std | 31.18 | | cv | 0.635 | | sampleLengths | | 0 | 122 | | 1 | 92 | | 2 | 81 | | 3 | 12 | | 4 | 62 | | 5 | 38 | | 6 | 7 | | 7 | 34 | | 8 | 56 | | 9 | 7 | | 10 | 113 | | 11 | 3 | | 12 | 74 | | 13 | 96 | | 14 | 46 | | 15 | 88 | | 16 | 34 | | 17 | 15 | | 18 | 18 | | 19 | 26 | | 20 | 42 | | 21 | 27 | | 22 | 74 | | 23 | 32 | | 24 | 40 | | 25 | 43 | | 26 | 78 | | 27 | 42 | | 28 | 11 | | 29 | 90 | | 30 | 63 | | 31 | 42 | | 32 | 43 | | 33 | 71 | | 34 | 13 | | 35 | 33 |
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| 81.34% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 88 | | matches | | 0 | "been closed" | | 1 | "were supposed" | | 2 | "been trimmed" | | 3 | "was clenched" | | 4 | "is hidden" | | 5 | "been sidelined" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 181 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 106 | | ratio | 0.057 | | matches | | 0 | "The air hit her first—cold, damp, carrying a mineral tang of old brickwork and something else, something burnt and organic that clung to the back of her throat." | | 1 | "The desk sergeant at Mornington Crescent had eyed her with a mix of pity and relief when he handed it over—a small disc of polished bone etched with a labyrinth pattern." | | 2 | "She had walked through, and her wristwatch had stuttered—a half-second pause before the second hand jumped back into its steady sweep." | | 3 | "She traced a line with her eyes from the dead man’s hand to the jars on the shelf—one of them had a hairline crack that wasn’t there in the photos the SOCO had taken twenty minutes earlier, because she’d glanced at the camera screen on her way in." | | 4 | "They formed a perimeter, yes, but also a bottleneck— a corridor of binding marks that funnelled from the stall entrance to the exact spot where the body lay." | | 5 | "Eva’s expression flickered—shock, then something harder, more guarded." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1069 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.02245088868101029 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.002806361085126286 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 16.68 | | std | 15.27 | | cv | 0.916 | | sampleLengths | | 0 | 27 | | 1 | 28 | | 2 | 43 | | 3 | 24 | | 4 | 4 | | 5 | 31 | | 6 | 21 | | 7 | 10 | | 8 | 21 | | 9 | 5 | | 10 | 5 | | 11 | 21 | | 12 | 18 | | 13 | 22 | | 14 | 2 | | 15 | 3 | | 16 | 10 | | 17 | 12 | | 18 | 2 | | 19 | 21 | | 20 | 6 | | 21 | 8 | | 22 | 15 | | 23 | 10 | | 24 | 21 | | 25 | 17 | | 26 | 7 | | 27 | 10 | | 28 | 24 | | 29 | 10 | | 30 | 10 | | 31 | 24 | | 32 | 12 | | 33 | 7 | | 34 | 8 | | 35 | 105 | | 36 | 3 | | 37 | 12 | | 38 | 13 | | 39 | 49 | | 40 | 6 | | 41 | 13 | | 42 | 28 | | 43 | 36 | | 44 | 13 | | 45 | 8 | | 46 | 38 | | 47 | 7 | | 48 | 13 | | 49 | 40 |
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| 48.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.330188679245283 | | totalSentences | 106 | | uniqueOpeners | 35 | |
| 40.65% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 82 | | matches | | 0 | "Only a platform arch that" |
| | ratio | 0.012 | |
| 98.05% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 82 | | matches | | 0 | "he’d said, and then, quieter," | | 1 | "She had walked through, and" | | 2 | "She filed the glitch away." | | 3 | "His eyes were open, fixed" | | 4 | "His right hand was clenched" | | 5 | "She tucked a strand of" | | 6 | "It was old, the brass" | | 7 | "She delivered it with the" | | 8 | "Her military bearing kept her" | | 9 | "She let her gaze drift" | | 10 | "She had eighteen years of" | | 11 | "Her partner, DS Morris, had" | | 12 | "She remembered the way Morris’s" | | 13 | "She reached for the compass." | | 14 | "She held it flat on" | | 15 | "Her tone was flat, but" | | 16 | "She’d been sidelined from major" | | 17 | "She looked down at the" | | 18 | "She walked the scene, counting." | | 19 | "She traced a line with" |
| | ratio | 0.305 | |
| 14.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 82 | | matches | | 0 | "The bone token felt greasy" | | 1 | "The air hit her first—cold," | | 2 | "Camden Town’s abandoned deep-level shelter" | | 3 | "The Veil Market, the uniformed" | | 4 | "Quinn pocketed the token." | | 5 | "The desk sergeant at Mornington" | | 6 | "he’d said, and then, quieter," | | 7 | "She had walked through, and" | | 8 | "She filed the glitch away." | | 9 | "A body lay sprawled near" | | 10 | "The victim was male, late" | | 11 | "His eyes were open, fixed" | | 12 | "His right hand was clenched" | | 13 | "A woman’s voice, carrying the" | | 14 | "A figure emerged from behind" | | 15 | "Freckles dusted her nose and" | | 16 | "A worn leather satchel bulged" | | 17 | "She tucked a strand of" | | 18 | "The other cradled a notebook" | | 19 | "A faint grimace" |
| | ratio | 0.89 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 82 | | matches | | 0 | "Now she scanned the scene." | | 1 | "Now she understood the desk" |
| | ratio | 0.024 | |
| 65.64% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 4 | | matches | | 0 | "Her military bearing kept her spine straight, hands resting loose at her sides." | | 1 | "She let her gaze drift across the stall, noting the way the glass jars nearest the body were dim, the liquids inside darkened as though scorched from within." | | 2 | "The forensics team had set up their equipment around the perimeter, but every time a camera flash went off near the body, the light seemed to bend, as if passin…" | | 3 | "Her partner, DS Morris, had died three years ago in a warehouse that showed the same contradictions: a locked room, a body with no trauma, electronic failures, …" |
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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 | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 35 | | tagDensity | 0.171 | | leniency | 0.343 | | rawRatio | 0.167 | | effectiveRatio | 0.057 | |