| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.21% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1088 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "sharply" | | 1 | "cautiously" | | 2 | "nervously" |
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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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1088 | | totalAiIsms | 35 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | | | 23 | | | 24 | |
| | highlights | | 0 | "reminder" | | 1 | "scanned" | | 2 | "flickered" | | 3 | "racing" | | 4 | "resolve" | | 5 | "footsteps" | | 6 | "echoed" | | 7 | "rhythmic" | | 8 | "depths" | | 9 | "oppressive" | | 10 | "silence" | | 11 | "scanning" | | 12 | "etched" | | 13 | "intricate" | | 14 | "raced" | | 15 | "stark" | | 16 | "familiar" | | 17 | "pang" | | 18 | "cacophony" | | 19 | "symphony" | | 20 | "unwavering" | | 21 | "disrupt" | | 22 | "palpable" | | 23 | "potential" | | 24 | "navigated" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 2 | | found | | 0 | | label | "heart pounded in chest" | | count | 2 |
| | 1 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "heart pounded in her chest" | | 1 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 88 | | matches | | 0 | "filled with fear" | | 1 | "d with fear" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 88 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1086 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 55.66% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1060 | | uniqueNames | 10 | | maxNameDensity | 1.89 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 20 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Tube | 2 | | Camden | 1 | | Veil | 2 | | Market | 2 | | One | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "One" |
| | places | | | globalScore | 0.557 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | 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 | 1086 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 63.85% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 41.77 | | std | 15.6 | | cv | 0.373 | | sampleLengths | | 0 | 55 | | 1 | 72 | | 2 | 68 | | 3 | 57 | | 4 | 54 | | 5 | 46 | | 6 | 48 | | 7 | 59 | | 8 | 58 | | 9 | 65 | | 10 | 44 | | 11 | 37 | | 12 | 20 | | 13 | 20 | | 14 | 48 | | 15 | 36 | | 16 | 18 | | 17 | 30 | | 18 | 33 | | 19 | 34 | | 20 | 42 | | 21 | 33 | | 22 | 23 | | 23 | 32 | | 24 | 36 | | 25 | 18 |
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| 89.31% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 88 | | matches | | 0 | "was involved" | | 1 | "was undeterred" | | 2 | "was undeterred" | | 3 | "was undeterred" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 169 | | matches | | 0 | "was speaking" | | 1 | "was speaking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 91 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1062 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.014124293785310734 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.00847457627118644 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 11.93 | | std | 5.02 | | cv | 0.421 | | sampleLengths | | 0 | 16 | | 1 | 13 | | 2 | 26 | | 3 | 14 | | 4 | 18 | | 5 | 14 | | 6 | 26 | | 7 | 17 | | 8 | 11 | | 9 | 16 | | 10 | 24 | | 11 | 6 | | 12 | 9 | | 13 | 13 | | 14 | 13 | | 15 | 16 | | 16 | 12 | | 17 | 15 | | 18 | 4 | | 19 | 1 | | 20 | 1 | | 21 | 21 | | 22 | 11 | | 23 | 8 | | 24 | 10 | | 25 | 8 | | 26 | 9 | | 27 | 20 | | 28 | 14 | | 29 | 14 | | 30 | 15 | | 31 | 11 | | 32 | 10 | | 33 | 12 | | 34 | 11 | | 35 | 7 | | 36 | 13 | | 37 | 20 | | 38 | 18 | | 39 | 10 | | 40 | 7 | | 41 | 14 | | 42 | 13 | | 43 | 21 | | 44 | 19 | | 45 | 12 | | 46 | 13 | | 47 | 14 | | 48 | 14 | | 49 | 9 |
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| 43.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.18681318681318682 | | totalSentences | 91 | | uniqueOpeners | 17 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 86 | | matches | | 0 | "Her worn leather watch ticked" | | 1 | "She dodged a group of" | | 2 | "Her eyes, sharp and focused," | | 3 | "She knew the risks of" | | 4 | "She pushed forward, her resolve" | | 5 | "Her footsteps echoed in the" | | 6 | "Her hand instinctively moved to" | | 7 | "She followed, descending into the" | | 8 | "Her senses heightened, every sound" | | 9 | "She spotted him near a" | | 10 | "He was speaking with a" | | 11 | "She felt a familiar pang" | | 12 | "She hesitated, her instincts warning" | | 13 | "She slipped through the curtain," | | 14 | "She felt a surge of" | | 15 | "She needed to act, to" | | 16 | "Her decision made, she stepped" | | 17 | "He hesitated, his gaze flickering" | | 18 | "She moved closer, her presence" | | 19 | "She closed the distance between" |
| | ratio | 0.244 | |
| 18.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 86 | | matches | | 0 | "Detective Harlow Quinn sprinted through" | | 1 | "Her worn leather watch ticked" | | 2 | "The suspect, a shadowy figure" | | 3 | "Quinn's heart pounded in her" | | 4 | "She dodged a group of" | | 5 | "Her eyes, sharp and focused," | | 6 | "The neon lights of The" | | 7 | "The suspect turned sharply, slipping" | | 8 | "Quinn hesitated for a fraction" | | 9 | "The Veil Market was notorious," | | 10 | "She knew the risks of" | | 11 | "She pushed forward, her resolve" | | 12 | "The alley was narrow, the" | | 13 | "Her footsteps echoed in the" | | 14 | "The suspect was just ahead," | | 15 | "Quinn's instincts screamed at her" | | 16 | "The air was thick with" | | 17 | "Copper stung her nostrils." | | 18 | "Her hand instinctively moved to" | | 19 | "The suspect slipped through the" |
| | ratio | 0.884 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 92.73% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 4 | | matches | | 0 | "The suspect turned sharply, slipping into an alley that led to the abandoned Tube station beneath Camden." | | 1 | "The Veil Market was notorious, a hidden supernatural black market that moved locations every full moon." | | 2 | "The supernatural elements of the market were a stark reminder of the case that had cost her partner his life." | | 3 | "The scent of incense mingled with the metallic tang of blood, creating a heady mix that threatened to overwhelm her senses." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 1 | | matches | | 0 | "the suspect said, his voice tense" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |