| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 20 | | tagDensity | 0.45 | | leniency | 0.9 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 807 | | 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) | |
| 25.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 807 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "treacherous" | | 1 | "weight" | | 2 | "footsteps" | | 3 | "echoing" | | 4 | "pulse" | | 5 | "charged" | | 6 | "whisper" | | 7 | "unreadable" | | 8 | "flickered" | | 9 | "flicked" | | 10 | "jaw clenched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 78 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 78 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 90 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 792 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 48.11% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 687 | | uniqueNames | 10 | | maxNameDensity | 2.04 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 14 | | Raven | 1 | | Nest | 1 | | Tomás | 1 | | Herrera | 12 | | Tube | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Tomás" | | 4 | "Herrera" | | 5 | "Market" |
| | places | | | globalScore | 0.481 | | windowScore | 0.667 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 3 | | matches | | 0 | "as if waiting" | | 1 | "looked like glass vials of liquid moonlig" | | 2 | "quite music" |
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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 | 792 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 90 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 22 | | std | 16.56 | | cv | 0.753 | | sampleLengths | | 0 | 70 | | 1 | 17 | | 2 | 59 | | 3 | 45 | | 4 | 41 | | 5 | 28 | | 6 | 23 | | 7 | 14 | | 8 | 11 | | 9 | 25 | | 10 | 48 | | 11 | 3 | | 12 | 27 | | 13 | 46 | | 14 | 3 | | 15 | 29 | | 16 | 10 | | 17 | 12 | | 18 | 40 | | 19 | 2 | | 20 | 36 | | 21 | 8 | | 22 | 18 | | 23 | 13 | | 24 | 29 | | 25 | 16 | | 26 | 16 | | 27 | 13 | | 28 | 11 | | 29 | 7 | | 30 | 7 | | 31 | 25 | | 32 | 3 | | 33 | 20 | | 34 | 13 | | 35 | 4 |
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| 96.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 78 | | matches | | 0 | "were lined" | | 1 | "was yanked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 126 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 90 | | ratio | 0.1 | | matches | | 0 | "The suspect—Tomás Herrera, according to her intel—darted around a corner with the agility of someone who knew these streets better than she did." | | 1 | "She slammed through after him, into a dim stairwell that reeked of mildew and something sharper—ozone, maybe, or the metallic tang of old magic." | | 2 | "The air here was different—thick, charged." | | 3 | "The tunnel opened into a cavernous space—an abandoned Tube station, its vaulted ceiling lost in shadow." | | 4 | "The air smelled of incense and something darker—burning herbs, maybe, or the coppery hint of blood." | | 5 | "Quinn spun, reaching for her weapon, but the figure—tall, draped in a moth-eaten cloak—shook their head." | | 6 | "The market swallowed her, the noise rising—vendors hawking their wares, the clink of strange coins, the low hum of something that wasn’t quite music." | | 7 | "A noise outside—footsteps, too many, moving fast." | | 8 | "She had a choice now—fight, or run." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 704 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.026988636363636364 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005681818181818182 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 90 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 90 | | mean | 8.8 | | std | 5.89 | | cv | 0.669 | | sampleLengths | | 0 | 19 | | 1 | 28 | | 2 | 23 | | 3 | 12 | | 4 | 5 | | 5 | 19 | | 6 | 23 | | 7 | 17 | | 8 | 7 | | 9 | 3 | | 10 | 24 | | 11 | 11 | | 12 | 12 | | 13 | 13 | | 14 | 6 | | 15 | 6 | | 16 | 4 | | 17 | 7 | | 18 | 6 | | 19 | 5 | | 20 | 10 | | 21 | 16 | | 22 | 7 | | 23 | 5 | | 24 | 9 | | 25 | 11 | | 26 | 5 | | 27 | 16 | | 28 | 4 | | 29 | 13 | | 30 | 19 | | 31 | 16 | | 32 | 3 | | 33 | 7 | | 34 | 14 | | 35 | 6 | | 36 | 20 | | 37 | 2 | | 38 | 6 | | 39 | 2 | | 40 | 2 | | 41 | 14 | | 42 | 3 | | 43 | 5 | | 44 | 16 | | 45 | 8 | | 46 | 3 | | 47 | 7 | | 48 | 8 | | 49 | 4 |
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| 59.63% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.37777777777777777 | | totalSentences | 90 | | uniqueOpeners | 34 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 70 | | matches | | 0 | "She pushed harder, her breath" | | 1 | "Her wristwatch, its leather band" | | 2 | "She slammed through after him," | | 3 | "She slowed, hand hovering near" | | 4 | "she called, her voice steady" | | 5 | "He laughed, low and humorless." | | 6 | "She’d heard whispers of it," | | 7 | "She stepped forward." | | 8 | "She yanked free." | | 9 | "He turned as Quinn entered," | | 10 | "she shot back" | | 11 | "Her fingers flexed near her" | | 12 | "He sighed, rubbing the scar" | | 13 | "Her throat tightened." | | 14 | "they said, voice like gravel" | | 15 | "She had a choice now—fight," |
| | ratio | 0.229 | |
| 17.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 70 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn sprinted after" | | 2 | "The suspect—Tomás Herrera, according to" | | 3 | "Quinn barked, her voice cutting" | | 4 | "Herrera didn’t even glance back." | | 5 | "She pushed harder, her breath" | | 6 | "Her wristwatch, its leather band" | | 7 | "The alley narrowed, walls pressing" | | 8 | "Herrera disappeared through a rusted" | | 9 | "Quinn didn’t hesitate." | | 10 | "She slammed through after him," | | 11 | "The steps spiraled downward, the" | | 12 | "The walls were lined with" | | 13 | "Quinn’s pulse hammered in her" | | 14 | "This wasn’t just some back" | | 15 | "This was something else." | | 16 | "She slowed, hand hovering near" | | 17 | "The air here was different—thick," | | 18 | "A whisper of movement ahead." | | 19 | "Herrera’s silhouette paused at a" |
| | ratio | 0.886 | |
| 71.43% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 70 | | matches | | 0 | "Before she could answer, he" |
| | ratio | 0.014 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 5 | | matches | | 0 | "Detective Harlow Quinn sprinted after the figure in the dark hoodie, her boots splashing through oily puddles that reflected the green glow of The Raven's Nest …" | | 1 | "The suspect—Tomás Herrera, according to her intel—darted around a corner with the agility of someone who knew these streets better than she did." | | 2 | "She slammed through after him, into a dim stairwell that reeked of mildew and something sharper—ozone, maybe, or the metallic tang of old magic." | | 3 | "Herrera’s silhouette paused at a junction, half-turned, as if waiting." | | 4 | "The market swallowed her, the noise rising—vendors hawking their wares, the clink of strange coins, the low hum of something that wasn’t quite music." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn barked, her voice cutting through the drumming rain" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn barked (bark)" | | 1 | "the woman hissed (hiss)" | | 2 | "Herrera muttered (mutter)" |
| | dialogueSentences | 20 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0.5 | | effectiveRatio | 0.3 | |