| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said aloud [aloud]" |
| | dialogueSentences | 23 | | tagDensity | 0.348 | | leniency | 0.696 | | rawRatio | 0.125 | | effectiveRatio | 0.087 | |
| 85.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1729 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slowly" | | 1 | "slightly" | | 2 | "very" | | 3 | "softly" | | 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) | |
| 56.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1729 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "measured" | | 1 | "aftermath" | | 2 | "etched" | | 3 | "weight" | | 4 | "synthetic" | | 5 | "trembled" | | 6 | "magnetic" | | 7 | "flicked" | | 8 | "shimmered" | | 9 | "familiar" | | 10 | "silence" | | 11 | "spectral" | | 12 | "mechanical" |
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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 | 99 | | matches | (empty) | |
| 85.14% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 99 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 64 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1723 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 1 | | matches | | 0 | "Behind her, Ellis muttered about wasting time on ghost stories, but his voice sounded distant, unimportant." |
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| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 1210 | | uniqueNames | 10 | | maxNameDensity | 0.99 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Eva" | | discoveredNames | | Harlow | 2 | | Quinn | 12 | | Tube | 1 | | Camden | 1 | | Ellis | 9 | | Kowalski | 2 | | Eva | 11 | | Morris | 2 | | Victorian | 1 | | Detective | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Ellis" | | 3 | "Kowalski" | | 4 | "Eva" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 1 | | windowScore | 0.667 | |
| 52.60% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 77 | | glossingSentenceCount | 3 | | matches | | 0 | "felt like a market that had been frozen" | | 1 | "felt like a shutter pulled down against" | | 2 | "something like reluctant respect" |
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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 | 1723 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 59.41 | | std | 29.71 | | cv | 0.5 | | sampleLengths | | 0 | 115 | | 1 | 115 | | 2 | 54 | | 3 | 109 | | 4 | 58 | | 5 | 91 | | 6 | 54 | | 7 | 69 | | 8 | 19 | | 9 | 27 | | 10 | 46 | | 11 | 80 | | 12 | 58 | | 13 | 104 | | 14 | 66 | | 15 | 30 | | 16 | 67 | | 17 | 62 | | 18 | 59 | | 19 | 42 | | 20 | 60 | | 21 | 22 | | 22 | 11 | | 23 | 19 | | 24 | 81 | | 25 | 49 | | 26 | 19 | | 27 | 96 | | 28 | 41 |
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| 98.17% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 99 | | matches | | 0 | "been frozen" | | 1 | "been heated" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 209 | | matches | | 0 | "was willing" | | 1 | "was beginning" |
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| 42.61% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 2 | | flaggedSentences | 4 | | totalSentences | 114 | | ratio | 0.035 | | matches | | 0 | "The market had clearly been trading when violence struck; the stalls suggested dozens of people, yet only one set of fresh prints led away from the body toward a bricked-up archway at the far end of the platform." | | 1 | "The most valuable-looking items—stoppered bottles containing liquid that still shimmered with inner light—remained untouched." | | 2 | "The compass, the sigils, the insufficient blood, the untouched valuables, the impossible needle—all of it pointed away from the simple narrative Ellis wanted." | | 3 | "The nervous habit had stopped; in its place was something like reluctant respect." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 684 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.029239766081871343 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.01023391812865497 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 15.11 | | std | 11.18 | | cv | 0.74 | | sampleLengths | | 0 | 30 | | 1 | 24 | | 2 | 28 | | 3 | 33 | | 4 | 15 | | 5 | 35 | | 6 | 10 | | 7 | 16 | | 8 | 21 | | 9 | 8 | | 10 | 10 | | 11 | 16 | | 12 | 8 | | 13 | 30 | | 14 | 5 | | 15 | 13 | | 16 | 29 | | 17 | 11 | | 18 | 5 | | 19 | 6 | | 20 | 2 | | 21 | 38 | | 22 | 4 | | 23 | 54 | | 24 | 3 | | 25 | 14 | | 26 | 11 | | 27 | 11 | | 28 | 15 | | 29 | 10 | | 30 | 6 | | 31 | 21 | | 32 | 5 | | 33 | 8 | | 34 | 8 | | 35 | 10 | | 36 | 23 | | 37 | 9 | | 38 | 22 | | 39 | 21 | | 40 | 17 | | 41 | 8 | | 42 | 11 | | 43 | 5 | | 44 | 22 | | 45 | 6 | | 46 | 7 | | 47 | 33 | | 48 | 12 | | 49 | 5 |
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| 62.28% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.39473684210526316 | | totalSentences | 114 | | uniqueOpeners | 45 | |
| 34.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 96 | | matches | | 0 | "Instead they sat like offerings." |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 96 | | matches | | 0 | "Her boots rang sharp against" | | 1 | "It felt like a market" | | 2 | "he said, offering a curt" | | 3 | "She checked her worn leather" | | 4 | "She had heard Ellis's brand" | | 5 | "She reached for an object" | | 6 | "It trembled, then locked toward" | | 7 | "She turned the instrument slowly." | | 8 | "She slipped the compass into" | | 9 | "She tucked a stray curl" | | 10 | "She rose, keeping the compass" | | 11 | "She tucked the curl again." | | 12 | "She walked the perimeter of" | | 13 | "She returned to Eva." | | 14 | "She held the bagged instrument" | | 15 | "She had never believed them." | | 16 | "She crossed to the bricked" | | 17 | "She ran her fingers across" | | 18 | "she said aloud, piecing the" | | 19 | "She had spent three years" |
| | ratio | 0.25 | |
| 32.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 96 | | matches | | 0 | "Detective Harlow Quinn descended the" | | 1 | "Her boots rang sharp against" | | 2 | "The call had come in" | | 3 | "The platform opened before her" | | 4 | "Vials of luminous liquid glinted" | | 5 | "This was no" | | 6 | "It felt like a market" | | 7 | "Sergeant Ellis waited near the" | | 8 | "he said, offering a curt" | | 9 | "Quinn crouched beside the corpse." | | 10 | "The man had fallen backward" | | 11 | "The wounds were ugly, yet" | | 12 | "Blood had leaked, but not" | | 13 | "That was the first discrepancy." | | 14 | "She checked her worn leather" | | 15 | "The market had clearly been" | | 16 | "Ellis shifted his weight." | | 17 | "Quinn said nothing." | | 18 | "She had heard Ellis's brand" | | 19 | "Tonight it felt like a" |
| | ratio | 0.854 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 96 | | matches | | 0 | "Now the same metallic scent" | | 1 | "Now, in the cold light" |
| | ratio | 0.021 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 3 | | matches | | 0 | "At forty-one, with closely cropped salt-and-pepper hair and a sharp jaw that rarely softened, she had learned to trust the prickle that crawled across her scalp…" | | 1 | "Strange metal talismans etched with symbols she could not name lay beside coins that looked minted from no currency she recognised." | | 2 | "It trembled, then locked toward the bricked archway with an unnatural steadiness, as though the wall itself exerted a magnetic pull." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva said, voice low but steady" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 23 | | tagDensity | 0.261 | | leniency | 0.522 | | rawRatio | 0.167 | | effectiveRatio | 0.087 | |