| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 116 | | tagDensity | 0.164 | | leniency | 0.328 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1837 | | 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) | |
| 86.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1837 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "measured" | | 1 | "weight" | | 2 | "pulse" | | 3 | "trembled" | | 4 | "scanned" |
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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 | 175 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 175 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 272 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1835 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 89 | | wordCount | 1221 | | uniqueNames | 14 | | maxNameDensity | 2.29 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Eva" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Tube | 1 | | Harlow | 1 | | Quinn | 28 | | Detective | 2 | | Constable | 1 | | Martin | 1 | | Bell | 28 | | Kowalski | 1 | | Vale | 5 | | Eva | 17 | | Latin | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Constable" | | 3 | "Martin" | | 4 | "Bell" | | 5 | "Kowalski" | | 6 | "Vale" | | 7 | "Eva" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.353 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.545 | | wordCount | 1835 | | matches | | 0 | "not the cold of stone, but a depth" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 272 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 170 | | mean | 10.79 | | std | 10.71 | | cv | 0.992 | | sampleLengths | | 0 | 32 | | 1 | 20 | | 2 | 15 | | 3 | 6 | | 4 | 4 | | 5 | 48 | | 6 | 15 | | 7 | 32 | | 8 | 4 | | 9 | 11 | | 10 | 1 | | 11 | 17 | | 12 | 4 | | 13 | 5 | | 14 | 7 | | 15 | 3 | | 16 | 1 | | 17 | 11 | | 18 | 11 | | 19 | 30 | | 20 | 35 | | 21 | 4 | | 22 | 6 | | 23 | 2 | | 24 | 26 | | 25 | 4 | | 26 | 4 | | 27 | 4 | | 28 | 6 | | 29 | 10 | | 30 | 1 | | 31 | 18 | | 32 | 8 | | 33 | 1 | | 34 | 9 | | 35 | 10 | | 36 | 8 | | 37 | 12 | | 38 | 9 | | 39 | 42 | | 40 | 19 | | 41 | 3 | | 42 | 4 | | 43 | 43 | | 44 | 37 | | 45 | 45 | | 46 | 4 | | 47 | 3 | | 48 | 14 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 175 | | matches | | 0 | "were soaked" | | 1 | "been burned" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 222 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 272 | | ratio | 0.007 | | matches | | 0 | "The station smelled of rust, wet concrete, and something sweet beneath it all—a scent like bruised apples left in a cupboard." | | 1 | "Cold pressed through her glove—not the cold of stone, but a depth that reached past it." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1227 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.015484922575387123 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0024449877750611247 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 272 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 272 | | mean | 6.75 | | std | 4.36 | | cv | 0.647 | | sampleLengths | | 0 | 24 | | 1 | 8 | | 2 | 10 | | 3 | 10 | | 4 | 4 | | 5 | 11 | | 6 | 6 | | 7 | 4 | | 8 | 11 | | 9 | 11 | | 10 | 5 | | 11 | 21 | | 12 | 15 | | 13 | 10 | | 14 | 22 | | 15 | 4 | | 16 | 11 | | 17 | 1 | | 18 | 17 | | 19 | 4 | | 20 | 5 | | 21 | 7 | | 22 | 3 | | 23 | 1 | | 24 | 7 | | 25 | 4 | | 26 | 11 | | 27 | 14 | | 28 | 7 | | 29 | 9 | | 30 | 2 | | 31 | 10 | | 32 | 7 | | 33 | 16 | | 34 | 4 | | 35 | 2 | | 36 | 4 | | 37 | 2 | | 38 | 26 | | 39 | 4 | | 40 | 4 | | 41 | 4 | | 42 | 3 | | 43 | 3 | | 44 | 10 | | 45 | 1 | | 46 | 18 | | 47 | 8 | | 48 | 1 | | 49 | 2 |
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| 49.63% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.31985294117647056 | | totalSentences | 272 | | uniqueOpeners | 87 | |
| 68.97% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 145 | | matches | | 0 | "Only damp tiles and a" | | 1 | "Too shallow for a trail." | | 2 | "Somewhere behind the tiled wall," |
| | ratio | 0.021 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 145 | | matches | | 0 | "Her boots struck each step" | | 1 | "He led her back to" | | 2 | "Her leather watch pressed against" | | 3 | "She examined the lock without" | | 4 | "They passed through the ticket" | | 5 | "Their glare broke across the" | | 6 | "He wore a charcoal suit," | | 7 | "His throat had been cut" | | 8 | "Her curly red hair had" | | 9 | "She tucked a strand behind" | | 10 | "His left fist clenched around" | | 11 | "She pointed to the platform" | | 12 | "He stared at her." | | 13 | "His bare feet showed no" | | 14 | "Her satchel had a smear" | | 15 | "Its leather cover had split" | | 16 | "It weighed more than it" | | 17 | "It carried the same sweet" | | 18 | "She picked it up with" | | 19 | "It looked burned rather than" |
| | ratio | 0.221 | |
| 39.31% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 122 | | totalSentences | 145 | | matches | | 0 | "Rain slicked the iron steps" | | 1 | "Detective Harlow Quinn descended without" | | 2 | "Her boots struck each step" | | 3 | "Quinn reached the bottom and" | | 4 | "CAMDEN HIGH LEVEL flaked across" | | 5 | "Water dripped through the ceiling." | | 6 | "The station smelled of rust," | | 7 | "Bell came down beside her," | | 8 | "Quinn looked at him." | | 9 | "Quinn took two steps towards" | | 10 | "Bell caught her sleeve." | | 11 | "He led her back to" | | 12 | "The padlock lay on the" | | 13 | "Her leather watch pressed against" | | 14 | "She examined the lock without" | | 15 | "Dust coated the concrete beneath" | | 16 | "Bell leaned closer." | | 17 | "Bell glanced into the darkness" | | 18 | "Bell gave her a thin" | | 19 | "They passed through the ticket" |
| | ratio | 0.841 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 145 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 19 | | fancyCount | 3 | | fancyTags | | 0 | "he muttered (mutter)" | | 1 | "Eva whispered (whisper)" | | 2 | "Bell warned (warn)" |
| | dialogueSentences | 116 | | tagDensity | 0.164 | | leniency | 0.328 | | rawRatio | 0.158 | | effectiveRatio | 0.052 | |