| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn stepped further [further]" |
| | dialogueSentences | 58 | | tagDensity | 0.138 | | leniency | 0.276 | | rawRatio | 0.125 | | effectiveRatio | 0.034 | |
| 97.46% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1968 | | 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) | |
| 82.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1968 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "familiar" | | 1 | "streaming" | | 2 | "glint" | | 3 | "flicked" | | 4 | "weight" | | 5 | "pulse" |
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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 | 173 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 173 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 223 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1968 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1478 | | uniqueNames | 16 | | maxNameDensity | 1.69 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 25 | | Greek | 1 | | Street | 1 | | Static | 1 | | Soho | 2 | | Raven | 2 | | Nest | 2 | | Tomás | 17 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Water | 2 | | Underground | 1 | | Morris | 1 | | One | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Tomás" | | 5 | "Herrera" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Water" | | 9 | "Underground" | | 10 | "Morris" | | 11 | "One" |
| | places | | | globalScore | 0.654 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 109 | | glossingSentenceCount | 1 | | matches | | 0 | "as if checking the room" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.508 | | wordCount | 1968 | | matches | | 0 | "not from caution but from a change in the air" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 223 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 118 | | mean | 16.68 | | std | 17 | | cv | 1.019 | | sampleLengths | | 0 | 48 | | 1 | 53 | | 2 | 8 | | 3 | 2 | | 4 | 14 | | 5 | 60 | | 6 | 40 | | 7 | 4 | | 8 | 10 | | 9 | 51 | | 10 | 15 | | 11 | 2 | | 12 | 23 | | 13 | 7 | | 14 | 12 | | 15 | 5 | | 16 | 7 | | 17 | 67 | | 18 | 35 | | 19 | 65 | | 20 | 7 | | 21 | 49 | | 22 | 10 | | 23 | 39 | | 24 | 9 | | 25 | 58 | | 26 | 6 | | 27 | 14 | | 28 | 3 | | 29 | 53 | | 30 | 55 | | 31 | 14 | | 32 | 7 | | 33 | 7 | | 34 | 2 | | 35 | 4 | | 36 | 5 | | 37 | 6 | | 38 | 39 | | 39 | 11 | | 40 | 15 | | 41 | 4 | | 42 | 34 | | 43 | 2 | | 44 | 7 | | 45 | 12 | | 46 | 5 | | 47 | 17 | | 48 | 14 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 173 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 257 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 223 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1486 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small coin-sized object" |
| | adverbCount | 42 | | adverbRatio | 0.02826379542395693 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.004037685060565276 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 223 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 223 | | mean | 8.83 | | std | 6.46 | | cv | 0.732 | | sampleLengths | | 0 | 11 | | 1 | 15 | | 2 | 22 | | 3 | 13 | | 4 | 1 | | 5 | 1 | | 6 | 2 | | 7 | 2 | | 8 | 15 | | 9 | 19 | | 10 | 8 | | 11 | 2 | | 12 | 14 | | 13 | 6 | | 14 | 16 | | 15 | 12 | | 16 | 7 | | 17 | 12 | | 18 | 7 | | 19 | 24 | | 20 | 9 | | 21 | 7 | | 22 | 4 | | 23 | 2 | | 24 | 5 | | 25 | 3 | | 26 | 6 | | 27 | 15 | | 28 | 8 | | 29 | 4 | | 30 | 4 | | 31 | 6 | | 32 | 4 | | 33 | 4 | | 34 | 11 | | 35 | 4 | | 36 | 2 | | 37 | 10 | | 38 | 13 | | 39 | 1 | | 40 | 6 | | 41 | 12 | | 42 | 5 | | 43 | 7 | | 44 | 13 | | 45 | 21 | | 46 | 5 | | 47 | 14 | | 48 | 9 | | 49 | 5 |
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| 55.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.36771300448430494 | | totalSentences | 223 | | uniqueOpeners | 82 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 151 | | matches | | 0 | "Then he vaulted a stack" | | 1 | "Then a clipped answer from" | | 2 | "Somewhere in the room a" | | 3 | "Too quick for most people." | | 4 | "Then she took the first" |
| | ratio | 0.033 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 151 | | matches | | 0 | "He clutched something under his" | | 1 | "Her voice cracked along the" | | 2 | "He skidded around a delivery" | | 3 | "Her leather watch stuck to" | | 4 | "She blinked it clear and" | | 5 | "She ignored him." | | 6 | "He moved like he knew" | | 7 | "He wasn’t running blind." | | 8 | "He had a destination." | | 9 | "Her radio hissed at her" | | 10 | "She slapped it once." | | 11 | "She cut the radio and" | | 12 | "Her soles hit wet tarmac" | | 13 | "She fed it no attention." | | 14 | "He veered towards Soho’s broken" | | 15 | "She saw the green neon" | | 16 | "It never was." | | 17 | "She felt it every time" | | 18 | "She climbed the two wet" | | 19 | "He wore a dark shirt" |
| | ratio | 0.245 | |
| 75.89% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 116 | | totalSentences | 151 | | matches | | 0 | "Rain needled the city and" | | 1 | "Soho glimmered under it, every" | | 2 | "Detective Harlow Quinn cut between" | | 3 | "He clutched something under his" | | 4 | "Quinn hit the alley mouth" | | 5 | "Her voice cracked along the" | | 6 | "The man’s trainers slapped through" | | 7 | "He skidded around a delivery" | | 8 | "Quinn hurdled the crate, one" | | 9 | "Her leather watch stuck to" | | 10 | "Water ran off her cropped" | | 11 | "She blinked it clear and" | | 12 | "Quinn followed with less room" | | 13 | "A man swore at her." | | 14 | "She ignored him." | | 15 | "The suspect had gained ten" | | 16 | "He moved like he knew" | | 17 | "Quinn watched his choices instead" | | 18 | "He wasn’t running blind." | | 19 | "He had a destination." |
| | ratio | 0.768 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 151 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 3 | | matches | | 0 | "Missing persons who reappeared with blood in their cuffs and no memory worth taking." | | 1 | "A pair of men at a back table looked into their pints as if the foam required study." | | 2 | "Far below, somewhere under the city’s ribs, sound drifted up: metal clinking, a murmur of voices, one sharp laugh that broke like glass." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 58 | | tagDensity | 0.121 | | leniency | 0.241 | | rawRatio | 0.143 | | effectiveRatio | 0.034 | |