| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 141 | | tagDensity | 0.064 | | leniency | 0.128 | | rawRatio | 0.111 | | effectiveRatio | 0.014 | |
| 97.81% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2288 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 75.96% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2288 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "measured" | | 1 | "familiar" | | 2 | "grave" | | 3 | "flicked" | | 4 | "weight" | | 5 | "efficient" | | 6 | "coded" | | 7 | "flicker" | | 8 | "silence" | | 9 | "pulsed" | | 10 | "eyebrow" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 155 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 155 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 286 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2288 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 109 | | wordCount | 1341 | | uniqueNames | 10 | | maxNameDensity | 3.21 | | worstName | "Aurora" | | maxWindowNameDensity | 6 | | worstWindowName | "Aurora" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Soho | 1 | | Golden | 1 | | Empress | 1 | | Silas | 14 | | Aurora | 43 | | London | 1 | | Nia | 42 | | Rain | 3 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Aurora" | | 4 | "Nia" | | 5 | "Rain" |
| | places | | 0 | "Soho" | | 1 | "Golden" | | 2 | "London" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 99 | | 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 | 2288 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 286 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 180 | | mean | 12.71 | | std | 13.95 | | cv | 1.098 | | sampleLengths | | 0 | 75 | | 1 | 80 | | 2 | 10 | | 3 | 20 | | 4 | 8 | | 5 | 4 | | 6 | 19 | | 7 | 7 | | 8 | 10 | | 9 | 20 | | 10 | 7 | | 11 | 4 | | 12 | 13 | | 13 | 14 | | 14 | 4 | | 15 | 72 | | 16 | 5 | | 17 | 26 | | 18 | 18 | | 19 | 1 | | 20 | 23 | | 21 | 9 | | 22 | 1 | | 23 | 14 | | 24 | 58 | | 25 | 47 | | 26 | 3 | | 27 | 8 | | 28 | 19 | | 29 | 3 | | 30 | 7 | | 31 | 10 | | 32 | 16 | | 33 | 3 | | 34 | 12 | | 35 | 14 | | 36 | 4 | | 37 | 15 | | 38 | 15 | | 39 | 6 | | 40 | 2 | | 41 | 8 | | 42 | 9 | | 43 | 42 | | 44 | 12 | | 45 | 8 | | 46 | 19 | | 47 | 7 | | 48 | 3 | | 49 | 4 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 155 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 235 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 286 | | ratio | 0.003 | | matches | | 0 | "Someone at the other end of the bar dropped a spoon; the sound rang out and vanished." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1347 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 45 | | adverbRatio | 0.0334075723830735 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.002969561989606533 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 286 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 286 | | mean | 8 | | std | 6.95 | | cv | 0.869 | | sampleLengths | | 0 | 23 | | 1 | 22 | | 2 | 8 | | 3 | 22 | | 4 | 24 | | 5 | 18 | | 6 | 10 | | 7 | 28 | | 8 | 10 | | 9 | 8 | | 10 | 12 | | 11 | 8 | | 12 | 4 | | 13 | 6 | | 14 | 13 | | 15 | 7 | | 16 | 10 | | 17 | 16 | | 18 | 4 | | 19 | 7 | | 20 | 4 | | 21 | 13 | | 22 | 12 | | 23 | 2 | | 24 | 4 | | 25 | 12 | | 26 | 11 | | 27 | 14 | | 28 | 14 | | 29 | 7 | | 30 | 7 | | 31 | 7 | | 32 | 5 | | 33 | 6 | | 34 | 2 | | 35 | 2 | | 36 | 5 | | 37 | 11 | | 38 | 18 | | 39 | 1 | | 40 | 4 | | 41 | 19 | | 42 | 9 | | 43 | 1 | | 44 | 6 | | 45 | 8 | | 46 | 8 | | 47 | 28 | | 48 | 5 | | 49 | 5 |
| |
| 46.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.26223776223776224 | | totalSentences | 286 | | uniqueOpeners | 75 | |
| 23.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 141 | | matches | | 0 | "Then she crossed the floor." |
| | ratio | 0.007 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 141 | | matches | | 0 | "Her fingers wrapped around a" | | 1 | "She watched rain work down" | | 2 | "She paused under the green" | | 3 | "He reached for another glass" | | 4 | "She walked like she expected" | | 5 | "Her mouth still had that" | | 6 | "She stopped there." | | 7 | "He moved away before either" | | 8 | "She stood with one hand" | | 9 | "It gave her something to" | | 10 | "It came out fuller than" | | 11 | "She straightened and rubbed her" | | 12 | "He did not look up," | | 13 | "It cracked the surface and" | | 14 | "She glanced at Aurora, then" | | 15 | "He moved off again." | | 16 | "She did not ask which" | | 17 | "Her gaze drifted to Aurora’s" |
| | ratio | 0.128 | |
| 6.10% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 128 | | totalSentences | 141 | | matches | | 0 | "Men with dead cigarettes in" | | 1 | "Aurora stood at the far" | | 2 | "The smell of soy and" | | 3 | "Her fingers wrapped around a" | | 4 | "She watched rain work down" | | 5 | "Silas set a fresh kettle" | | 6 | "The silver signet ring on" | | 7 | "Aurora tipped the mug towards" | | 8 | "Silas took the mug from" | | 9 | "Steam curled between them." | | 10 | "Aurora slid onto the seat" | | 11 | "The door opened on a" | | 12 | "A woman stepped in, dragging" | | 13 | "She paused under the green" | | 14 | "Water shone on her hair," | | 15 | "A leather briefcase hung from" | | 16 | "The coat sat clean through" | | 17 | "Everything about her looked pressed," | | 18 | "Aurora glanced up, then stopped." | | 19 | "A voice laughing through cigarette" |
| | ratio | 0.908 | |
| 35.46% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 141 | | matches | | 0 | "Now her suit jacket fit" |
| | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 1 | | matches | | 0 | "Men with dead cigarettes in black-and-white photographs stared down through the dim light as if they still held secrets in their cheeks." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 3 | | fancyTags | | 0 | "Nia murmured (murmur)" | | 1 | "she repeated (repeat)" | | 2 | "Nia murmured (murmur)" |
| | dialogueSentences | 141 | | tagDensity | 0.028 | | leniency | 0.057 | | rawRatio | 0.75 | | effectiveRatio | 0.043 | |