| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1023 | | 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) | |
| 65.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1023 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "calculated" | | 1 | "rhythmic" | | 2 | "predictable" | | 3 | "navigating" | | 4 | "electric" | | 5 | "scanned" | | 6 | "resolved" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "without second thought" | | count | 1 |
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| | highlights | | 0 | "without a second thought" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 92 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 92 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 94 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 4 | | totalWords | 1019 | | ratio | 0.004 | | matches | | 0 | "you're going rogue again" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 999 | | uniqueNames | 14 | | maxNameDensity | 0.9 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 9 | | Raven | 2 | | Nest | 2 | | Vauxhall | 1 | | Wardour | 1 | | Street | 1 | | Chambers | 1 | | Soho | 1 | | Camden | 2 | | Lock | 1 | | Bridge | 1 | | Northern | 1 | | Morris | 1 | | Peckham | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Chambers" | | 3 | "Morris" |
| | places | | 0 | "Vauxhall" | | 1 | "Wardour" | | 2 | "Street" | | 3 | "Soho" | | 4 | "Camden" | | 5 | "Lock" | | 6 | "Bridge" | | 7 | "Peckham" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1019 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 94 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 29.97 | | std | 27.54 | | cv | 0.919 | | sampleLengths | | 0 | 10 | | 1 | 67 | | 2 | 3 | | 3 | 70 | | 4 | 33 | | 5 | 19 | | 6 | 97 | | 7 | 10 | | 8 | 22 | | 9 | 18 | | 10 | 68 | | 11 | 26 | | 12 | 6 | | 13 | 49 | | 14 | 2 | | 15 | 60 | | 16 | 42 | | 17 | 5 | | 18 | 56 | | 19 | 2 | | 20 | 92 | | 21 | 17 | | 22 | 69 | | 23 | 3 | | 24 | 49 | | 25 | 5 | | 26 | 6 | | 27 | 8 | | 28 | 37 | | 29 | 4 | | 30 | 20 | | 31 | 29 | | 32 | 10 | | 33 | 5 |
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| 97.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 92 | | matches | | 0 | "been closed" | | 1 | "been transformed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 172 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 94 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1003 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.038883349950149554 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006979062811565304 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 94 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 94 | | mean | 10.84 | | std | 7.65 | | cv | 0.706 | | sampleLengths | | 0 | 10 | | 1 | 23 | | 2 | 2 | | 3 | 11 | | 4 | 12 | | 5 | 19 | | 6 | 3 | | 7 | 14 | | 8 | 24 | | 9 | 11 | | 10 | 2 | | 11 | 6 | | 12 | 13 | | 13 | 25 | | 14 | 7 | | 15 | 1 | | 16 | 5 | | 17 | 4 | | 18 | 10 | | 19 | 9 | | 20 | 33 | | 21 | 27 | | 22 | 8 | | 23 | 3 | | 24 | 17 | | 25 | 5 | | 26 | 3 | | 27 | 2 | | 28 | 20 | | 29 | 2 | | 30 | 18 | | 31 | 4 | | 32 | 4 | | 33 | 14 | | 34 | 35 | | 35 | 11 | | 36 | 17 | | 37 | 3 | | 38 | 6 | | 39 | 6 | | 40 | 2 | | 41 | 4 | | 42 | 26 | | 43 | 17 | | 44 | 2 | | 45 | 5 | | 46 | 15 | | 47 | 15 | | 48 | 7 | | 49 | 18 |
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| 80.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5 | | totalSentences | 94 | | uniqueOpeners | 47 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 81 | | matches | | 0 | "Then he ran." | | 1 | "Once, at 3 a.m., a" | | 2 | "Then he disappeared into the" | | 3 | "Somewhere below, the sound of" | | 4 | "Then at the suspect, three" |
| | ratio | 0.062 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 81 | | matches | | 0 | "She'd clocked him twenty minutes" | | 1 | "He was younger than her." | | 2 | "She'd been watching The Raven's" | | 3 | "She'd written that one up." | | 4 | "He knew the streets." | | 5 | "She'd give him that." | | 6 | "He took short turns, never" | | 7 | "She followed the sounds as" | | 8 | "He didn't stop." | | 9 | "He slipped down a set" | | 10 | "She knew this station." | | 11 | "She'd walked past it hundreds" | | 12 | "Her hand found the railing." | | 13 | "She'd found his warrant card" | | 14 | "She still had his photo" | | 15 | "They looked at her the" | | 16 | "She scanned the crowd for" | | 17 | "She spotted him at a" | | 18 | "He didn't seem aggressive." | | 19 | "He seemed the way bouncers" |
| | ratio | 0.296 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 81 | | matches | | 0 | "The suspect bolted the moment" | | 1 | "She'd clocked him twenty minutes" | | 2 | "A canvas bag worn against" | | 3 | "The kind of man who'd" | | 4 | "Quinn was already sprinting, her" | | 5 | "The rain came sideways on" | | 6 | "The suspect cut left into" | | 7 | "Quinn vaulted one and kept" | | 8 | "He was younger than her." | | 9 | "She'd been watching The Raven's" | | 10 | "The bar in Soho with" | | 11 | "Items changed hands." | | 12 | "She'd written that one up." | | 13 | "The alley spat them both" | | 14 | "Quinn radioed in her position," | | 15 | "He knew the streets." | | 16 | "She'd give him that." | | 17 | "He took short turns, never" | | 18 | "She followed the sounds as" | | 19 | "Camden Lock Bridge came and" |
| | ratio | 0.716 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 76.41% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 4 | | matches | | 0 | "She'd clocked him twenty minutes earlier, loitering outside The Raven's Nest with the particular stillness of someone who didn't want to be noticed." | | 1 | "Quinn was already sprinting, her boots hitting wet pavement in a hard, rhythmic crack." | | 2 | "Lanterns, she realised, or something that functioned as lanterns, casting a bruised amber glow over a space that had no business being as large as it was." | | 3 | "The old platform had been transformed into something that resembled a souk crossed with an evidence locker." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |