| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.60% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 974 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "slowly" | | 2 | "really" |
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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) | |
| 23.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 974 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "echoing" | | 1 | "flicker" | | 2 | "raced" | | 3 | "pounding" | | 4 | "determined" | | 5 | "trepidation" | | 6 | "treacherous" | | 7 | "silence" | | 8 | "resolve" | | 9 | "weight" | | 10 | "could feel" |
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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 | 1 | | narrationSentences | 79 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 79 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 79 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 983 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 937 | | uniqueNames | 14 | | maxNameDensity | 0.96 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 2 | | Harlow | 2 | | Quinn | 9 | | Records | 1 | | Sure | 1 | | Thursday | 1 | | Soho | 1 | | London | 2 | | Silas | 3 | | Camden | 1 | | Marlene | 1 | | Julian | 2 | | Morris | 1 | | Imperial | 1 |
| | persons | | 0 | "Detective" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Records" | | 4 | "Silas" | | 5 | "Marlene" | | 6 | "Julian" | | 7 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Camden" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 983 | | matches | (empty) | |
| 82.28% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 79 | | matches | | 0 | "felt that thundering" | | 1 | "signaled that the" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 18 | | mean | 54.61 | | std | 28.35 | | cv | 0.519 | | sampleLengths | | 0 | 87 | | 1 | 70 | | 2 | 43 | | 3 | 19 | | 4 | 46 | | 5 | 30 | | 6 | 27 | | 7 | 85 | | 8 | 56 | | 9 | 35 | | 10 | 48 | | 11 | 128 | | 12 | 73 | | 13 | 19 | | 14 | 90 | | 15 | 46 | | 16 | 52 | | 17 | 29 |
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| 91.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 79 | | matches | | 0 | "been spotted" | | 1 | "was killed" | | 2 | "was killed" |
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| 46.74% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 174 | | matches | | 0 | "was getting" | | 1 | "was getting" | | 2 | "was opening" | | 3 | "was already fading" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 79 | | ratio | 0.076 | | matches | | 0 | "The suspect - a man in a long black coat with his hood pulled up - had been spotted exiting Silas' bar earlier this evening, known in some circles as The Raven's Nest." | | 1 | "She tried another angle, scoped the room, and when she knew - she knew - the perp had slipped out, she'd burst out of the bar, leaving Silas to stare after her in confusion." | | 2 | "Without warning, she'd heard a shot - and then silence." | | 3 | "The man pulled it open and stepped forward - but it was immediately apparent to Harlow that this was no ordinary door." | | 4 | "There was no knob, no handle - the portal seemed to have vanished after closing." | | 5 | "She took a last look at the portal - but it was already fading from view, becoming nothing more than another entry The detective, shivering, shook her head and stepped away, the cold rain and the blurred fog settling into her bones as she jogged away, pistol snap back into place." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 129 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 2 | | adverbRatio | 0.015503875968992248 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.015503875968992248 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 79 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 79 | | mean | 12.43 | | std | 8.84 | | cv | 0.711 | | sampleLengths | | 0 | 23 | | 1 | 13 | | 2 | 28 | | 3 | 23 | | 4 | 33 | | 5 | 15 | | 6 | 13 | | 7 | 9 | | 8 | 8 | | 9 | 12 | | 10 | 9 | | 11 | 14 | | 12 | 19 | | 13 | 12 | | 14 | 34 | | 15 | 12 | | 16 | 12 | | 17 | 6 | | 18 | 11 | | 19 | 16 | | 20 | 17 | | 21 | 4 | | 22 | 5 | | 23 | 2 | | 24 | 9 | | 25 | 2 | | 26 | 14 | | 27 | 6 | | 28 | 26 | | 29 | 5 | | 30 | 4 | | 31 | 9 | | 32 | 5 | | 33 | 5 | | 34 | 3 | | 35 | 11 | | 36 | 14 | | 37 | 19 | | 38 | 16 | | 39 | 36 | | 40 | 8 | | 41 | 4 | | 42 | 8 | | 43 | 7 | | 44 | 8 | | 45 | 10 | | 46 | 7 | | 47 | 2 | | 48 | 7 | | 49 | 4 |
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| 66.24% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4430379746835443 | | totalSentences | 79 | | uniqueOpeners | 35 | |
| 88.89% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 75 | | matches | | 0 | "Just after six a.m., the" | | 1 | "More of a portal." |
| | ratio | 0.027 | |
| 81.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 75 | | matches | | 0 | "Her carefully polished leather shoes" | | 1 | "She knew more went on" | | 2 | "She'd slipped inside, searching the" | | 3 | "he'd called with similar acquiescence" | | 4 | "She tried another angle, scoped" | | 5 | "Her prey was directly ahead," | | 6 | "She shouted, but the man" | | 7 | "She chased after him, but" | | 8 | "They raced from street to" | | 9 | "They were in Camden now." | | 10 | "It smelled of mildew and" | | 11 | "He was getting away." | | 12 | "Her gut screamed." | | 13 | "Her partner's memories haunted her," | | 14 | "She felt that thundering thumping" | | 15 | "She clenched her eyes shut" | | 16 | "She had been tracking a" | | 17 | "She remembered the police tape" | | 18 | "Her hand closed around the" | | 19 | "She didn't like guns." |
| | ratio | 0.347 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 53 | | totalSentences | 75 | | matches | | 0 | "The rain pounded the cobbled" | | 1 | "Her carefully polished leather shoes" | | 2 | "Another gust of wind tousled" | | 3 | "The worn leather watch on" | | 4 | "The suspect - a man" | | 5 | "She knew more went on" | | 6 | "She'd slipped inside, searching the" | | 7 | "The walls were a dizzying" | | 8 | "he'd called with similar acquiescence" | | 9 | "Silas replied, turning his spa" | | 10 | "She tried another angle, scoped" | | 11 | "Quinn shot around the corner," | | 12 | "Her prey was directly ahead," | | 13 | "She shouted, but the man" | | 14 | "She chased after him, but" | | 15 | "They raced from street to" | | 16 | "Quinn mentally mapped it." | | 17 | "They were in Camden now." | | 18 | "The station was a maze" | | 19 | "The man slipped down a" |
| | ratio | 0.707 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 75 | | matches | | 0 | "If this was a trap," | | 1 | "If it was not, she" |
| | ratio | 0.027 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "She shouted, but the man didn't slow" | | 1 | "she called, her voice carrying down the corridor" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 5 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0.333 | | effectiveRatio | 0.333 | |