| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1072 | | 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) | |
| 72.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1072 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "whisper" | | 1 | "footsteps" | | 2 | "echo" | | 3 | "velvet" | | 4 | "scanned" |
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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 | 92 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 92 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1072 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 88.46% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 975 | | uniqueNames | 11 | | maxNameDensity | 1.23 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 12 | | Raven | 1 | | Nest | 2 | | Soho | 1 | | Berwick | 1 | | Street | 2 | | Brewer | 1 | | Vauxhall | 1 | | Camden | 1 | | Morris | 3 | | Victorian | 1 |
| | persons | | | places | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Soho" | | 3 | "Berwick" | | 4 | "Street" | | 5 | "Brewer" | | 6 | "Vauxhall" | | 7 | "Camden" |
| | globalScore | 0.885 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed steeper than they had on the way down" |
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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 | 1072 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 101 | | matches | | 0 | "learned that paperwork" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 30.63 | | std | 23.49 | | cv | 0.767 | | sampleLengths | | 0 | 13 | | 1 | 44 | | 2 | 3 | | 3 | 9 | | 4 | 67 | | 5 | 6 | | 6 | 71 | | 7 | 64 | | 8 | 9 | | 9 | 48 | | 10 | 9 | | 11 | 55 | | 12 | 37 | | 13 | 7 | | 14 | 43 | | 15 | 17 | | 16 | 1 | | 17 | 58 | | 18 | 15 | | 19 | 15 | | 20 | 82 | | 21 | 4 | | 22 | 52 | | 23 | 74 | | 24 | 18 | | 25 | 20 | | 26 | 15 | | 27 | 4 | | 28 | 27 | | 29 | 52 | | 30 | 13 | | 31 | 29 | | 32 | 43 | | 33 | 31 | | 34 | 17 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 92 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 164 | | matches | | 0 | "wasn't laughing" | | 1 | "was waiting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 101 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 976 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.028688524590163935 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0020491803278688526 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 10.61 | | std | 7.79 | | cv | 0.734 | | sampleLengths | | 0 | 13 | | 1 | 25 | | 2 | 19 | | 3 | 3 | | 4 | 2 | | 5 | 4 | | 6 | 3 | | 7 | 16 | | 8 | 16 | | 9 | 13 | | 10 | 4 | | 11 | 13 | | 12 | 5 | | 13 | 6 | | 14 | 10 | | 15 | 31 | | 16 | 4 | | 17 | 26 | | 18 | 8 | | 19 | 13 | | 20 | 43 | | 21 | 4 | | 22 | 5 | | 23 | 11 | | 24 | 8 | | 25 | 17 | | 26 | 5 | | 27 | 7 | | 28 | 9 | | 29 | 4 | | 30 | 16 | | 31 | 3 | | 32 | 12 | | 33 | 5 | | 34 | 6 | | 35 | 9 | | 36 | 19 | | 37 | 9 | | 38 | 9 | | 39 | 7 | | 40 | 27 | | 41 | 7 | | 42 | 9 | | 43 | 6 | | 44 | 1 | | 45 | 9 | | 46 | 1 | | 47 | 1 | | 48 | 17 | | 49 | 12 |
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| 61.39% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4158415841584158 | | totalSentences | 101 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 83 | | matches | | 0 | "Of course he didn't." | | 1 | "Somewhere below, water dripped with" | | 2 | "Then she heard music." | | 3 | "Somewhere a goat screamed with" | | 4 | "Just a hundred strangers who" | | 5 | "Too many teeth was a" |
| | ratio | 0.072 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 83 | | matches | | 0 | "He'd been leaning against the" | | 1 | "They never did." | | 2 | "Her voice came back off" | | 3 | "He didn't break stride." | | 4 | "She'd come to the Nest" | | 5 | "She'd followed worse on less." | | 6 | "He turned north, toward Camden," | | 7 | "She'd learned that paperwork lesson" | | 8 | "He held it like a" | | 9 | "He reached the old station" | | 10 | "She heard his footsteps change" | | 11 | "Her torch beam cut into" | | 12 | "She keyed the radio back" | | 13 | "She looked at the signal" | | 14 | "He was getting away, or" | | 15 | "She counted forty steps, then" | | 16 | "Her watch face fogged." | | 17 | "She checked it anyway, out" | | 18 | "She kept her face the" | | 19 | "Her heart hammered anyway." |
| | ratio | 0.253 | |
| 68.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 83 | | matches | | 0 | "The man ran before Quinn" | | 1 | "He'd been leaning against the" | | 2 | "They never did." | | 3 | "Rain needled down through the" | | 4 | "The suspect cut left into" | | 5 | "Quinn vaulted the toppled plastic," | | 6 | "Morris used to laugh at" | | 7 | "Morris wasn't laughing anywhere now." | | 8 | "Her voice came back off" | | 9 | "The man ducked under a" | | 10 | "He didn't break stride." | | 11 | "Quinn did, one hand flat" | | 12 | "She'd come to the Nest" | | 13 | "A name, an address, a" | | 14 | "Guilt had a smell." | | 15 | "She'd followed worse on less." | | 16 | "He turned north, toward Camden," | | 17 | "Rain sheeted off the awnings" | | 18 | "Quinn's radio crackled at her" | | 19 | "She'd learned that paperwork lesson" |
| | ratio | 0.783 | |
| 60.24% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 83 | | matches | | 0 | "Now he was three streets" |
| | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 2 | | matches | | 0 | "The tile changed halfway, Victorian green giving way to stone that looked older than the city above it, carved with marks her beam slid off without catching." | | 1 | "The stairwell opened without warning onto a platform that shouldn't exist, and Quinn stepped out and forgot, for one full breath, how to be a detective." |
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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 | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.154 | | leniency | 0.308 | | rawRatio | 0 | | effectiveRatio | 0 | |