| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 38 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 75 | | tagDensity | 0.507 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.21% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1321 | | 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) | |
| 54.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1321 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "pulse" | | 1 | "synthetic" | | 2 | "echoed" | | 3 | "silence" | | 4 | "scanned" | | 5 | "etched" | | 6 | "flickered" | | 7 | "vibrated" | | 8 | "pulsed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 179 | | matches | (empty) | |
| 86.99% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 5 | | narrationSentences | 179 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 216 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 17 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1321 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 75 | | wordCount | 957 | | uniqueNames | 6 | | maxNameDensity | 4.39 | | worstName | "Harlow" | | maxWindowNameDensity | 6 | | worstWindowName | "Harlow" | | discoveredNames | | Eva | 29 | | Tube | 1 | | Camden | 1 | | Harlow | 42 | | Veil | 1 | | Compass | 1 |
| | persons | | | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 1 | | matches | | 0 | "coat that seemed to absorb the light" |
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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 | 1321 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 216 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 85 | | mean | 15.54 | | std | 11.38 | | cv | 0.732 | | sampleLengths | | 0 | 54 | | 1 | 32 | | 2 | 20 | | 3 | 29 | | 4 | 30 | | 5 | 41 | | 6 | 5 | | 7 | 32 | | 8 | 44 | | 9 | 5 | | 10 | 6 | | 11 | 7 | | 12 | 33 | | 13 | 12 | | 14 | 8 | | 15 | 9 | | 16 | 26 | | 17 | 4 | | 18 | 16 | | 19 | 18 | | 20 | 12 | | 21 | 35 | | 22 | 24 | | 23 | 22 | | 24 | 9 | | 25 | 1 | | 26 | 38 | | 27 | 11 | | 28 | 19 | | 29 | 1 | | 30 | 22 | | 31 | 10 | | 32 | 2 | | 33 | 26 | | 34 | 17 | | 35 | 29 | | 36 | 3 | | 37 | 28 | | 38 | 6 | | 39 | 11 | | 40 | 30 | | 41 | 4 | | 42 | 25 | | 43 | 6 | | 44 | 13 | | 45 | 20 | | 46 | 16 | | 47 | 4 | | 48 | 2 | | 49 | 28 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 179 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 202 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 216 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 957 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.01567398119122257 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0041797283176593526 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 216 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 216 | | mean | 6.12 | | std | 3.52 | | cv | 0.575 | | sampleLengths | | 0 | 15 | | 1 | 4 | | 2 | 1 | | 3 | 1 | | 4 | 17 | | 5 | 2 | | 6 | 2 | | 7 | 12 | | 8 | 17 | | 9 | 15 | | 10 | 6 | | 11 | 7 | | 12 | 7 | | 13 | 4 | | 14 | 14 | | 15 | 11 | | 16 | 8 | | 17 | 14 | | 18 | 8 | | 19 | 5 | | 20 | 12 | | 21 | 10 | | 22 | 14 | | 23 | 5 | | 24 | 8 | | 25 | 10 | | 26 | 14 | | 27 | 4 | | 28 | 11 | | 29 | 10 | | 30 | 7 | | 31 | 5 | | 32 | 7 | | 33 | 5 | | 34 | 2 | | 35 | 4 | | 36 | 7 | | 37 | 8 | | 38 | 7 | | 39 | 10 | | 40 | 8 | | 41 | 5 | | 42 | 7 | | 43 | 8 | | 44 | 7 | | 45 | 2 | | 46 | 4 | | 47 | 8 | | 48 | 4 | | 49 | 10 |
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| 40.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.2777777777777778 | | totalSentences | 216 | | uniqueOpeners | 60 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 127 | | matches | (empty) | | ratio | 0 | |
| 90.87% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 127 | | matches | | 0 | "She pressed two fingers against" | | 1 | "She tucked a curl of" | | 2 | "Her voice echoed in the" | | 3 | "She pulled a latex glove" | | 4 | "She reached into her worn" | | 5 | "She shone her torch on" | | 6 | "She stepped closer, her boots" | | 7 | "She walked to the victim's" | | 8 | "It lay open, palm up." | | 9 | "She held it up to" | | 10 | "She turned the casing." | | 11 | "She examined the wound on" | | 12 | "She ran her gloved finger" | | 13 | "She walked to the wall" | | 14 | "She pressed her torch against" | | 15 | "She checked the magazine." | | 16 | "She reached into her satchel" | | 17 | "It took the shape of" | | 18 | "It wore a long coat" | | 19 | "Her voice was tight." |
| | ratio | 0.323 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 125 | | totalSentences | 127 | | matches | | 0 | "Harlow knelt in the grime," | | 1 | "Copper stung her nostrils." | | 2 | "She pressed two fingers against" | | 3 | "The victim wore a cheap" | | 4 | "Eva stood a few paces" | | 5 | "She tucked a curl of" | | 6 | "Her voice echoed in the" | | 7 | "Harlow didn't look up." | | 8 | "She pulled a latex glove" | | 9 | "She reached into her worn" | | 10 | "Harlow stood, her knees cracking." | | 11 | "The worn leather watch on" | | 12 | "She shone her torch on" | | 13 | "The markings were indeed faintly" | | 14 | "She stepped closer, her boots" | | 15 | "Harlow scanned the perimeter." | | 16 | "The abandoned Tube station beneath" | | 17 | "Dust motes danced in the" | | 18 | "She walked to the victim's" | | 19 | "It lay open, palm up." |
| | ratio | 0.984 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 127 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 38 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 30 | | fancyCount | 5 | | fancyTags | | 0 | "Eva whispered (whisper)" | | 1 | "Harlow ordered (order)" | | 2 | "Eva whispered (whisper)" | | 3 | "Eva shouted (shout)" | | 4 | "Eva yelled (yell)" |
| | dialogueSentences | 75 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.167 | | effectiveRatio | 0.133 | |