| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 61 | | tagDensity | 0.066 | | leniency | 0.131 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2089 | | 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) | |
| 76.07% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2089 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "flickered" | | 1 | "footsteps" | | 2 | "shattered" | | 3 | "scanned" | | 4 | "echoed" | | 5 | "weight" | | 6 | "velvet" |
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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 | 1 | | narrationSentences | 232 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 232 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 289 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2089 | | ratio | 0 | | matches | (empty) | |
| 93.75% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 1 | | matches | | 0 | "No, Quinn corrected herself." |
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| 31.08% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 79 | | wordCount | 1850 | | uniqueNames | 14 | | maxNameDensity | 2.38 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 44 | | Camden | 1 | | Underground | 1 | | Vale | 3 | | Kentish | 1 | | Town | 1 | | Road | 1 | | London | 1 | | Elias | 17 | | Morris | 2 | | Southwark | 1 | | Mara | 3 | | Market | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Camden" | | 3 | "Underground" | | 4 | "Vale" | | 5 | "Elias" | | 6 | "Morris" | | 7 | "Mara" | | 8 | "Market" |
| | places | | 0 | "Kentish" | | 1 | "Town" | | 2 | "Road" | | 3 | "London" | | 4 | "Southwark" |
| | globalScore | 0.311 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 145 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like an eye sewn shut" |
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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 | 2089 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 289 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 197 | | mean | 10.6 | | std | 11.97 | | cv | 1.129 | | sampleLengths | | 0 | 13 | | 1 | 33 | | 2 | 5 | | 3 | 14 | | 4 | 47 | | 5 | 7 | | 6 | 48 | | 7 | 3 | | 8 | 17 | | 9 | 5 | | 10 | 1 | | 11 | 2 | | 12 | 9 | | 13 | 26 | | 14 | 3 | | 15 | 2 | | 16 | 9 | | 17 | 35 | | 18 | 62 | | 19 | 5 | | 20 | 28 | | 21 | 2 | | 22 | 10 | | 23 | 5 | | 24 | 4 | | 25 | 10 | | 26 | 45 | | 27 | 4 | | 28 | 6 | | 29 | 33 | | 30 | 5 | | 31 | 3 | | 32 | 25 | | 33 | 5 | | 34 | 8 | | 35 | 4 | | 36 | 2 | | 37 | 6 | | 38 | 5 | | 39 | 8 | | 40 | 3 | | 41 | 24 | | 42 | 9 | | 43 | 10 | | 44 | 25 | | 45 | 5 | | 46 | 29 | | 47 | 2 | | 48 | 6 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 232 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 318 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 289 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1853 | | adjectiveStacks | 2 | | stackExamples | | 0 | "small, grey-skinned man" | | 1 | "tall pressed against it" |
| | adverbCount | 47 | | adverbRatio | 0.025364274150026983 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0021586616297895305 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 289 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 289 | | mean | 7.23 | | std | 4.95 | | cv | 0.685 | | sampleLengths | | 0 | 13 | | 1 | 9 | | 2 | 10 | | 3 | 14 | | 4 | 5 | | 5 | 11 | | 6 | 3 | | 7 | 10 | | 8 | 30 | | 9 | 3 | | 10 | 4 | | 11 | 7 | | 12 | 15 | | 13 | 14 | | 14 | 9 | | 15 | 10 | | 16 | 3 | | 17 | 2 | | 18 | 3 | | 19 | 5 | | 20 | 7 | | 21 | 5 | | 22 | 1 | | 23 | 2 | | 24 | 9 | | 25 | 9 | | 26 | 17 | | 27 | 3 | | 28 | 2 | | 29 | 9 | | 30 | 13 | | 31 | 17 | | 32 | 5 | | 33 | 9 | | 34 | 5 | | 35 | 17 | | 36 | 8 | | 37 | 23 | | 38 | 5 | | 39 | 5 | | 40 | 16 | | 41 | 7 | | 42 | 2 | | 43 | 10 | | 44 | 5 | | 45 | 4 | | 46 | 10 | | 47 | 7 | | 48 | 7 | | 49 | 7 |
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| 51.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.3391003460207612 | | totalSentences | 289 | | uniqueOpeners | 98 | |
| 47.62% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 210 | | matches | | 0 | "Then he shoved an elderly" | | 1 | "Somewhere far below, a bell" | | 2 | "Then every bell in the" |
| | ratio | 0.014 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 210 | | matches | | 0 | "Her left boot struck a" | | 1 | "He wore a charcoal coat" | | 2 | "She ran with military precision," | | 3 | "He ran like someone following" | | 4 | "He glanced back." | | 5 | "Her shopping bag burst open," | | 6 | "He slipped into the alley." | | 7 | "She had left her radio" | | 8 | "She ran into the alley." | | 9 | "She drew her service pistol." | | 10 | "She moved sideways, shoulder against" | | 11 | "She nudged it with her" | | 12 | "His voice carried too clearly" | | 13 | "He stepped backwards." | | 14 | "He had disappeared." | | 15 | "Its metal lid leaned against" | | 16 | "It smelled of wet stone," | | 17 | "She reached the bottom and" | | 18 | "He lifted his chin." | | 19 | "She had never seen ash" |
| | ratio | 0.162 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 175 | | totalSentences | 210 | | matches | | 0 | "The man vaulted the bonnet" | | 1 | "Detective Harlow Quinn hit the" | | 2 | "Her left boot struck a" | | 3 | "The taxi driver leaned on" | | 4 | "The driver answered with a" | | 5 | "Quinn ignored both." | | 6 | "He wore a charcoal coat" | | 7 | "Nobody challenged him." | | 8 | "Nobody even looked surprised." | | 9 | "That bothered Quinn more than" | | 10 | "She ran with military precision," | | 11 | "This man did not flee" | | 12 | "He ran like someone following" | | 13 | "He glanced back." | | 14 | "A cut along his cheek." | | 15 | "A silver chain disappearing beneath" | | 16 | "Quinn raised her warrant card." | | 17 | "Quinn caught the woman before" | | 18 | "Her shopping bag burst open," | | 19 | "Quinn lowered her to the" |
| | ratio | 0.833 | |
| 23.81% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 210 | | matches | | 0 | "Now she stood alone in" |
| | ratio | 0.005 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 68 | | technicalSentenceCount | 3 | | matches | | 0 | "He wore a charcoal coat that flared behind him and a pale mask strapped over the back of his head, its blank face staring at the people he left behind." | | 1 | "Somewhere far below, a bell rang once, then again, as though someone had struck it underwater." | | 2 | "Mara Vale’s blood flashed in Quinn’s memory, black ash lifting from the wound as though gravity had reversed." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 61 | | tagDensity | 0.066 | | leniency | 0.131 | | rawRatio | 0.25 | | effectiveRatio | 0.033 | |