| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1198 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 16.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1198 | | totalAiIsms | 20 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "echoing" | | 1 | "flicker" | | 2 | "glint" | | 3 | "electric" | | 4 | "maw" | | 5 | "rhythmic" | | 6 | "scanning" | | 7 | "shimmered" | | 8 | "silence" | | 9 | "chaotic" | | 10 | "velvet" | | 11 | "tracing" | | 12 | "lilt" | | 13 | "effortless" | | 14 | "echoed" | | 15 | "porcelain" | | 16 | "racing" | | 17 | "pulsed" | | 18 | "flicked" |
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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 | 95 | | matches | (empty) | |
| 97.74% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 95 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1198 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1050 | | uniqueNames | 17 | | maxNameDensity | 1.33 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Soho | 2 | | Quinn | 1 | | Harlow | 14 | | Raven | 1 | | Nest | 1 | | Victorian | 1 | | Morris | 1 | | Veil | 1 | | Market | 1 | | Tube | 1 | | Camden | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 4 | | Herrera | 1 | | Lower | 1 | | Vaults | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Harlow" | | 2 | "Raven" | | 3 | "Morris" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Tomás" | | 7 | "Herrera" |
| | places | | | globalScore | 0.833 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like a giant heart beating beneath" |
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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 | 1198 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 106 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 26.62 | | std | 17.51 | | cv | 0.658 | | sampleLengths | | 0 | 2 | | 1 | 59 | | 2 | 51 | | 3 | 35 | | 4 | 33 | | 5 | 52 | | 6 | 31 | | 7 | 11 | | 8 | 62 | | 9 | 21 | | 10 | 36 | | 11 | 14 | | 12 | 48 | | 13 | 27 | | 14 | 26 | | 15 | 3 | | 16 | 38 | | 17 | 55 | | 18 | 33 | | 19 | 8 | | 20 | 12 | | 21 | 45 | | 22 | 11 | | 23 | 28 | | 24 | 12 | | 25 | 15 | | 26 | 53 | | 27 | 3 | | 28 | 31 | | 29 | 59 | | 30 | 8 | | 31 | 4 | | 32 | 32 | | 33 | 42 | | 34 | 12 | | 35 | 39 | | 36 | 24 | | 37 | 5 | | 38 | 14 | | 39 | 12 | | 40 | 19 | | 41 | 9 | | 42 | 18 | | 43 | 9 | | 44 | 37 |
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| 94.18% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 95 | | matches | | 0 | "were replaced" | | 1 | "were lined" | | 2 | "been overturned" |
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| 46.74% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 174 | | matches | | 0 | "was seeing" | | 1 | "wasn't running" | | 2 | "was fighting" | | 3 | "wasn't fleeing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 106 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1052 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, ivory-colored token" |
| | adverbCount | 20 | | adverbRatio | 0.019011406844106463 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006653992395437262 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 11.3 | | std | 6.8 | | cv | 0.602 | | sampleLengths | | 0 | 2 | | 1 | 14 | | 2 | 12 | | 3 | 9 | | 4 | 9 | | 5 | 15 | | 6 | 21 | | 7 | 11 | | 8 | 17 | | 9 | 2 | | 10 | 18 | | 11 | 3 | | 12 | 14 | | 13 | 8 | | 14 | 22 | | 15 | 3 | | 16 | 8 | | 17 | 19 | | 18 | 13 | | 19 | 12 | | 20 | 7 | | 21 | 11 | | 22 | 13 | | 23 | 10 | | 24 | 1 | | 25 | 3 | | 26 | 13 | | 27 | 13 | | 28 | 7 | | 29 | 3 | | 30 | 23 | | 31 | 4 | | 32 | 17 | | 33 | 8 | | 34 | 17 | | 35 | 11 | | 36 | 4 | | 37 | 10 | | 38 | 15 | | 39 | 4 | | 40 | 14 | | 41 | 15 | | 42 | 7 | | 43 | 20 | | 44 | 13 | | 45 | 13 | | 46 | 3 | | 47 | 17 | | 48 | 21 | | 49 | 17 |
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| 38.57% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.26666666666666666 | | totalSentences | 105 | | uniqueOpeners | 28 | |
| 37.04% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 90 | | matches | | 0 | "Further down the tunnel, the" |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 90 | | matches | | 0 | "He vaulted over a low" | | 1 | "She sprinted, her boots slapping" | | 2 | "She rounded a corner, her" | | 3 | "She jammed her shoulder into" | | 4 | "He sprinted toward a heavy" | | 5 | "He ripped the cover aside" | | 6 | "He dropped into the black" | | 7 | "She checked the worn leather" | | 8 | "She was alone." | | 9 | "She had seen the way" | | 10 | "She gripped the rungs." | | 11 | "It sounded like a giant" | | 12 | "She stood up and brushed" | | 13 | "She moved forward, her hand" | | 14 | "It was a sprawling, chaotic" | | 15 | "She kept her head down," | | 16 | "He wore a simple linen" | | 17 | "He looked her up and" | | 18 | "He wasn't running anymore." | | 19 | "He was fighting, his movements" |
| | ratio | 0.3 | |
| 21.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 79 | | totalSentences | 90 | | matches | | 0 | "The shout tore through the" | | 1 | "He vaulted over a low" | | 2 | "Harlow Quinn didn't waste breath" | | 3 | "She sprinted, her boots slapping" | | 4 | "The rhythm of the chase" | | 5 | "She rounded a corner, her" | | 6 | "The suspect slowed for a" | | 7 | "The man pivoted, sliding through" | | 8 | "Harlow didn't hesitate." | | 9 | "She jammed her shoulder into" | | 10 | "The alley opened into a" | | 11 | "The Raven's Nest." | | 12 | "The suspect didn't go for" | | 13 | "He sprinted toward a heavy" | | 14 | "He ripped the cover aside" | | 15 | "He dropped into the black" | | 16 | "Harlow reached the edge and" | | 17 | "A ladder of rusted rungs" | | 18 | "The scent of ozone and" | | 19 | "She checked the worn leather" |
| | ratio | 0.878 | |
| 55.56% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 90 | | matches | | 0 | "To the left, a distinctive" |
| | ratio | 0.011 | |
| 75.47% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 5 | | matches | | 0 | "She rounded a corner, her shoulder clipping a metal bin that clattered loudly, echoing off the narrow walls of the alley." | | 1 | "The walls were lined with smooth, obsidian-like stone that shimmered with an iridescent sheen." | | 2 | "Creatures that defied every law of biology haggled over crates of shimmering vials and bound leather books." | | 3 | "He snapped a wrist, threw a punch that sent a hooded man flying ten feet, and scrambled up a flight of stairs leading toward a darker, deeper level of the stati…" | | 4 | "The air was colder, the blue flames replaced by a suffocating, ink-black darkness that swallowed the light of her torch." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | 0 | "Harlow said, her voice a low rasp" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0 | | effectiveRatio | 0 | |