| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 21 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.65% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 787 | | 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) | |
| 36.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 787 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "echo" | | 1 | "gloom" | | 2 | "silence" | | 3 | "flicker" | | 4 | "glinting" | | 5 | "etched" | | 6 | "stomach" | | 7 | "trembled" | | 8 | "traced" | | 9 | "familiar" |
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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) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 85 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 100 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 781 | | ratio | 0.003 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 64.86% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 646 | | uniqueNames | 7 | | maxNameDensity | 1.7 | | worstName | "Cole" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Cole" | | discoveredNames | | Tube | 1 | | Sergeant | 1 | | Cole | 11 | | Quinn | 9 | | Eva | 1 | | Kowalski | 1 | | Morris | 2 |
| | persons | | 0 | "Sergeant" | | 1 | "Cole" | | 2 | "Quinn" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.649 | | windowScore | 0.833 | |
| 91.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 1 | | matches | | 0 | "something like this, Morris had died" |
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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 | 781 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 100 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 21.11 | | std | 16.66 | | cv | 0.79 | | sampleLengths | | 0 | 68 | | 1 | 3 | | 2 | 32 | | 3 | 7 | | 4 | 48 | | 5 | 28 | | 6 | 20 | | 7 | 21 | | 8 | 59 | | 9 | 21 | | 10 | 23 | | 11 | 12 | | 12 | 33 | | 13 | 8 | | 14 | 17 | | 15 | 30 | | 16 | 6 | | 17 | 38 | | 18 | 29 | | 19 | 4 | | 20 | 11 | | 21 | 41 | | 22 | 3 | | 23 | 18 | | 24 | 6 | | 25 | 5 | | 26 | 30 | | 27 | 3 | | 28 | 50 | | 29 | 7 | | 30 | 10 | | 31 | 7 | | 32 | 6 | | 33 | 8 | | 34 | 27 | | 35 | 34 | | 36 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 85 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 119 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 100 | | ratio | 0.05 | | matches | | 0 | "\"Body’s in there. Male, late twenties. No ID, no wallet. Just this.\" He held up an evidence bag, the contents glinting under the artificial light—a small brass compass, its face etched with strange symbols." | | 1 | "Then—there." | | 2 | "One of them—a crescent moon bisected by a jagged line—looked familiar." | | 3 | "A draft whispered out, carrying the scent of old paper and something sharper—copper, maybe, or ozone." | | 4 | "Beyond it, the darkness shifted, coalescing into shapes—shelves, maybe, or stalls." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 652 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.03374233128834356 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0015337423312883436 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 100 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 100 | | mean | 7.81 | | std | 5.91 | | cv | 0.757 | | sampleLengths | | 0 | 10 | | 1 | 18 | | 2 | 22 | | 3 | 18 | | 4 | 3 | | 5 | 21 | | 6 | 7 | | 7 | 4 | | 8 | 4 | | 9 | 3 | | 10 | 7 | | 11 | 34 | | 12 | 7 | | 13 | 3 | | 14 | 4 | | 15 | 21 | | 16 | 16 | | 17 | 4 | | 18 | 19 | | 19 | 2 | | 20 | 12 | | 21 | 15 | | 22 | 5 | | 23 | 5 | | 24 | 3 | | 25 | 19 | | 26 | 11 | | 27 | 10 | | 28 | 3 | | 29 | 8 | | 30 | 5 | | 31 | 7 | | 32 | 7 | | 33 | 5 | | 34 | 4 | | 35 | 14 | | 36 | 15 | | 37 | 3 | | 38 | 5 | | 39 | 5 | | 40 | 12 | | 41 | 8 | | 42 | 22 | | 43 | 3 | | 44 | 3 | | 45 | 8 | | 46 | 13 | | 47 | 12 | | 48 | 1 | | 49 | 4 |
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| 58.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.37 | | totalSentences | 100 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 78 | | matches | | 0 | "Just a single, clean puncture" | | 1 | "Just cold, smooth ceramic." | | 2 | "Almost invisible, but when she" | | 3 | "Instead, she turned the compass" | | 4 | "Then it stopped." | | 5 | "Then she stepped through." |
| | ratio | 0.077 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 78 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "He waved her over, the" | | 2 | "She ignored the jab." | | 3 | "He held up an evidence" | | 4 | "She knew that compass." | | 5 | "She stepped closer, the beam" | | 6 | "She was too busy staring" | | 7 | "She stood, brushing dust from" | | 8 | "He handed her another evidence" | | 9 | "She turned the token over" | | 10 | "She ran her fingers along" | | 11 | "She dug her fingers in" | | 12 | "She didn’t look at him." | | 13 | "She’d seen it before, in" | | 14 | "She pressed her palm against" | | 15 | "She was too busy watching" | | 16 | "She just watched as the" | | 17 | "She shook him off." | | 18 | "She didn’t correct him." | | 19 | "She already knew that." |
| | ratio | 0.269 | |
| 81.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 78 | | matches | | 0 | "The abandoned Tube station smelled" | | 1 | "Quinn stepped off the last" | | 2 | "The beam of her torch" | | 3 | "She adjusted the worn leather" | | 4 | "Detective Sergeant Cole stood near" | | 5 | "He waved her over, the" | | 6 | "She ignored the jab." | | 7 | "Cole jerked his chin toward" | | 8 | "He held up an evidence" | | 9 | "The needle spun lazily, as" | | 10 | "Quinn’s fingers twitched." | | 11 | "She knew that compass." | | 12 | "She stepped closer, the beam" | | 13 | "Cole made a vague gesture" | | 14 | "The body lay sprawled across" | | 15 | "The floodlights bleached his skin" | | 16 | "Quinn crouched, her knees protesting." | | 17 | "Cole said, arms crossed" | | 18 | "Quinn didn’t answer." | | 19 | "She was too busy staring" |
| | ratio | 0.756 | |
| 64.10% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 78 | | matches | | 0 | "Now it pointed straight at" |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 21 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0.333 | | effectiveRatio | 0.095 | |