| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.565 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.02% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1432 | | totalAiIsmAdverbs | 2 | | 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) | |
| 19.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1432 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | |
| | highlights | | 0 | "measured" | | 1 | "rhythmic" | | 2 | "echoed" | | 3 | "dancing" | | 4 | "weight" | | 5 | "gloom" | | 6 | "silence" | | 7 | "standard" | | 8 | "scanning" | | 9 | "chaotic" | | 10 | "perfect" | | 11 | "oppressive" | | 12 | "crystalline" | | 13 | "flicker" | | 14 | "tangible" | | 15 | "intricate" | | 16 | "charm" | | 17 | "wavering" | | 18 | "etched" | | 19 | "profound" | | 20 | "racing" | | 21 | "pulsed" |
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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 | 85 | | matches | (empty) | |
| 75.63% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 85 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1428 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1147 | | uniqueNames | 10 | | maxNameDensity | 1.22 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Harlow | 1 | | Quinn | 14 | | Miller | 9 | | London | 1 | | Morris | 1 | | Metropolitan | 1 | | Police | 1 | | Bloomsbury | 1 | | Eva | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Miller" | | 3 | "Morris" | | 4 | "Police" | | 5 | "Eva" |
| | places | | | globalScore | 0.89 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 1 | | matches | | 0 | "patterns that seemed to shift if she looked at them too directly" |
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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 | 1428 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 40.8 | | std | 23.92 | | cv | 0.586 | | sampleLengths | | 0 | 74 | | 1 | 23 | | 2 | 84 | | 3 | 45 | | 4 | 11 | | 5 | 76 | | 6 | 49 | | 7 | 27 | | 8 | 44 | | 9 | 51 | | 10 | 25 | | 11 | 19 | | 12 | 94 | | 13 | 6 | | 14 | 41 | | 15 | 14 | | 16 | 30 | | 17 | 87 | | 18 | 37 | | 19 | 18 | | 20 | 51 | | 21 | 17 | | 22 | 37 | | 23 | 37 | | 24 | 51 | | 25 | 12 | | 26 | 2 | | 27 | 65 | | 28 | 39 | | 29 | 5 | | 30 | 55 | | 31 | 63 | | 32 | 47 | | 33 | 55 | | 34 | 37 |
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| 88.75% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 85 | | matches | | 0 | "was sprawled" | | 1 | "been stabbed" | | 2 | "was gathered" | | 3 | "been poured" | | 4 | "were curled" |
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| 50.19% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 178 | | matches | | 0 | "wasn't looking" | | 1 | "was looking" | | 2 | "wasn't behaving" | | 3 | "was failing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 2 | | flaggedSentences | 5 | | totalSentences | 95 | | ratio | 0.053 | | matches | | 0 | "She adjusted the sleeve of her jacket, the worn leather of her watch pressing against her left wrist—a grounding weight in a place that felt fundamentally untethered." | | 1 | "She didn't look at the blood first; she looked at the environment." | | 2 | "There were no footprints leading to the body—except for the ones made by the forensics team and Miller." | | 3 | "The carvings weren't just patterns; they were sigils, etched with a delicacy that suggested a master artisan rather than a street thug." | | 4 | "They would try to force it into a box—homicide, robbery, manslaughter—and in doing so, they would lose the truth." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1155 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.025108225108225107 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.011255411255411256 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 15.03 | | std | 9.53 | | cv | 0.634 | | sampleLengths | | 0 | 26 | | 1 | 25 | | 2 | 23 | | 3 | 23 | | 4 | 3 | | 5 | 27 | | 6 | 20 | | 7 | 30 | | 8 | 4 | | 9 | 18 | | 10 | 27 | | 11 | 11 | | 12 | 11 | | 13 | 21 | | 14 | 44 | | 15 | 10 | | 16 | 39 | | 17 | 14 | | 18 | 13 | | 19 | 11 | | 20 | 17 | | 21 | 16 | | 22 | 5 | | 23 | 12 | | 24 | 16 | | 25 | 18 | | 26 | 25 | | 27 | 11 | | 28 | 8 | | 29 | 7 | | 30 | 12 | | 31 | 6 | | 32 | 8 | | 33 | 17 | | 34 | 44 | | 35 | 6 | | 36 | 18 | | 37 | 23 | | 38 | 10 | | 39 | 4 | | 40 | 11 | | 41 | 19 | | 42 | 16 | | 43 | 4 | | 44 | 36 | | 45 | 25 | | 46 | 6 | | 47 | 9 | | 48 | 16 | | 49 | 12 |
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| 37.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.3263157894736842 | | totalSentences | 95 | | uniqueOpeners | 31 | |
| 41.15% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 81 | | matches | | 0 | "Instead of a wide, chaotic" |
| | ratio | 0.012 | |
| 27.41% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 81 | | matches | | 0 | "She adjusted the sleeve of" | | 1 | "She ignored the way the" | | 2 | "She had been a detective" | | 3 | "He looked tired, his expression" | | 4 | "He was sprawled on his" | | 5 | "He looked young, his features" | | 6 | "She knelt, her movements economical." | | 7 | "She didn't look at the" | | 8 | "She reached out, her gloved" | | 9 | "She wasn't looking at the" | | 10 | "She was looking at the" | | 11 | "she said, her voice dropping" | | 12 | "She thought of Morris." | | 13 | "She thought of the way" | | 14 | "She had spent three years" | | 15 | "She used a pair of" | | 16 | "She lifted it." | | 17 | "It wasn't a piece of" | | 18 | "It was a fragment of" | | 19 | "It was small, no larger" |
| | ratio | 0.481 | |
| 34.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 81 | | matches | | 0 | "The descent into the disused" | | 1 | "Detective Harlow Quinn kept her" | | 2 | "The air here was heavy," | | 3 | "DS Miller said, his flashlight" | | 4 | "Quinn didn't respond." | | 5 | "She adjusted the sleeve of" | | 6 | "She ignored the way the" | | 7 | "She had been a detective" | | 8 | "This was the latter." | | 9 | "The forensics team was a" | | 10 | "Quinn asked, her voice low" | | 11 | "Miller stepped into her path," | | 12 | "He looked tired, his expression" | | 13 | "Quinn moved past him, her" | | 14 | "Miller countered, gesturing vaguely toward" | | 15 | "Quinn stepped into the circle" | | 16 | "He was sprawled on his" | | 17 | "He looked young, his features" | | 18 | "She knelt, her movements economical." | | 19 | "She didn't look at the" |
| | ratio | 0.852 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 8 | | matches | | 0 | "Detective Harlow Quinn kept her pace measured, her boots striking the concrete with a rhythmic, military precision that echoed too loudly against the damp tiles…" | | 1 | "She adjusted the sleeve of her jacket, the worn leather of her watch pressing against her left wrist—a grounding weight in a place that felt fundamentally untet…" | | 2 | "As Quinn approached, the beam of her own light cut through the haze, illuminating the yellow tape that looked garish and absurd against the ancient, decaying br…" | | 3 | "He looked tired, his expression wearing the practiced boredom of a man who wanted this to be a simple paperwork exercise." | | 4 | "Instead of a wide, chaotic spray indicative of a struggle or a frantic movement, the dark crimson pool was gathered in a tight, unnaturally perfect circle aroun…" | | 5 | "She thought of the way the air had turned cold in that warehouse three years ago, the way the light had bent in ways that defied every law of physics she had sp…" | | 6 | "She had spent three years trying to rationalize his death, to find the logical thread that would tie his disappearance to a tangible, earthly cause." | | 7 | "She thought of the whispers she had heard in the corners of the city, the rumors of markets that existed in the folds of reality, places that moved with the moo…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 4 | | matches | | 0 | "Quinn asked, her voice low and steady" | | 1 | "she said, her voice dropping an octave" | | 2 | "Quinn said, more to herself than to Miller" | | 3 | "Miller said, though his voice lacked its earlier conviction" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 1 | | fancyTags | | 0 | "Quinn murmured (murmur)" |
| | dialogueSentences | 23 | | tagDensity | 0.435 | | leniency | 0.87 | | rawRatio | 0.1 | | effectiveRatio | 0.087 | |