| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 2 | | adverbTags | | 0 | "she asks finally [finally]" | | 1 | "He steps back [back]" |
| | dialogueSentences | 82 | | tagDensity | 0.256 | | leniency | 0.512 | | rawRatio | 0.095 | | effectiveRatio | 0.049 | |
| 72.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1618 | | totalAiIsmAdverbs | 9 | | found | | | highlights | | 0 | "precisely" | | 1 | "slightly" | | 2 | "really" |
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| 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) | |
| 56.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1618 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "glistening" | | 1 | "traced" | | 2 | "pulse" | | 3 | "stomach" | | 4 | "silence" | | 5 | "charged" | | 6 | "resolve" | | 7 | "familiar" | | 8 | "warmth" | | 9 | "flicker" | | 10 | "intricate" | | 11 | "race" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 76 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 76 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 137 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1638 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 28 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 1080 | | uniqueNames | 14 | | maxNameDensity | 0.56 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Angry" | | discoveredNames | | Aurora | 6 | | Moreau | 1 | | Silas | 1 | | Ptolemy | 1 | | Eva | 1 | | Merlin | 1 | | East | 1 | | End | 1 | | Brick | 1 | | Lane | 1 | | Camden | 1 | | King | 1 | | Cross | 1 | | Angry | 3 |
| | persons | | 0 | "Aurora" | | 1 | "Moreau" | | 2 | "Silas" | | 3 | "Eva" | | 4 | "Merlin" | | 5 | "King" | | 6 | "Cross" |
| | places | | 0 | "East" | | 1 | "End" | | 2 | "Brick" | | 3 | "Lane" | | 4 | "Camden" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | 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 | 1638 | | matches | (empty) | |
| 93.67% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 137 | | matches | | 0 | "hates that she" | | 1 | "hates that she" | | 2 | "say that night" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 82 | | mean | 19.98 | | std | 17.66 | | cv | 0.884 | | sampleLengths | | 0 | 43 | | 1 | 39 | | 2 | 16 | | 3 | 23 | | 4 | 11 | | 5 | 42 | | 6 | 13 | | 7 | 30 | | 8 | 92 | | 9 | 5 | | 10 | 9 | | 11 | 13 | | 12 | 26 | | 13 | 43 | | 14 | 9 | | 15 | 48 | | 16 | 23 | | 17 | 31 | | 18 | 15 | | 19 | 38 | | 20 | 9 | | 21 | 8 | | 22 | 66 | | 23 | 4 | | 24 | 20 | | 25 | 5 | | 26 | 18 | | 27 | 49 | | 28 | 2 | | 29 | 4 | | 30 | 4 | | 31 | 4 | | 32 | 2 | | 33 | 5 | | 34 | 19 | | 35 | 17 | | 36 | 8 | | 37 | 8 | | 38 | 16 | | 39 | 28 | | 40 | 4 | | 41 | 54 | | 42 | 3 | | 43 | 1 | | 44 | 59 | | 45 | 10 | | 46 | 2 | | 47 | 29 | | 48 | 29 | | 49 | 4 |
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| 91.41% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 76 | | matches | | 0 | "were supposed" | | 1 | "supposed" | | 2 | "was terrified " |
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| 58.16% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 188 | | matches | | 0 | "was trying" | | 1 | "was playing" | | 2 | "was lying" | | 3 | "was carrying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 20 | | semicolonCount | 0 | | flaggedSentences | 16 | | totalSentences | 137 | | ratio | 0.117 | | matches | | 0 | "The door swings open before she can second-guess herself, and Aurora finds herself staring up at a face she hasn't seen in three months — not since the night she walked out of his flat with her suitcase and her pride in tatters." | | 1 | "The door remains open behind her, and she can see straight through to the tiny kitchen where Ptolemy — no, this is her flat, not Eva's — where her own tabby, Merlin, watches from the windowsill with green eyes narrowed." | | 2 | "\"And?\" His amber eye — the one that's human, the one that used to crinkle when he was trying not to laugh — narrows slightly." | | 3 | "Marius — the name alone makes her skin crawl." | | 4 | "She can't help it — she still moves around him like she used to, careful not to catch her elbow on the doorframe, mindful of the space between them." | | 5 | "The flat smells like cardamom tea and old paper — she's been burning sage and reading too many books lately, trying to understand the symbols in the fragments she's found." | | 6 | "She remembers the last time he looked at her like this — like she was just another job, another piece on whatever board he was playing." | | 7 | "With the way she'd lied and said she wasn't afraid when really she was terrified — of him, of what he might become, of what she might become if she stayed." | | 8 | "Below, the streetlights cast long shadows across Brick Lane, and she can hear the distant hum of the city — life continuing while they stand here picking at old wounds." | | 9 | "He studies her for a long moment, those heterochromatic eyes — one amber, one black — reading her like a text she never meant to write." | | 10 | "She whirls around, and he's right — she is angry." | | 11 | "\"Of this.\" She gestures between them, encompassing everything — the secrets, the lies, the way they keep circling each other like predators who've forgotten how to hunt anything else." | | 12 | "\"Yes, you did.\" He reaches into his jacket pocket and pulls out a small photograph — them, standing outside that little café near King's Cross, both of them grinning like idiots." | | 13 | "She meets his gaze then, really meets it, and sees the truth there — the fear, the vulnerability, the parts of him he never shows anyone else." | | 14 | "The words are dramatic, typically him, but there's something raw underneath — something real." | | 15 | "She watches him walk toward the bookshelf — the one stacked with ancient texts and forbidden knowledge — and wonders when she started collecting things that could kill her." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 913 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.03723986856516977 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.009857612267250822 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 137 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 137 | | mean | 11.96 | | std | 10.09 | | cv | 0.844 | | sampleLengths | | 0 | 43 | | 1 | 29 | | 2 | 10 | | 3 | 16 | | 4 | 8 | | 5 | 8 | | 6 | 7 | | 7 | 11 | | 8 | 2 | | 9 | 40 | | 10 | 7 | | 11 | 6 | | 12 | 25 | | 13 | 5 | | 14 | 13 | | 15 | 35 | | 16 | 44 | | 17 | 5 | | 18 | 6 | | 19 | 3 | | 20 | 3 | | 21 | 9 | | 22 | 1 | | 23 | 26 | | 24 | 8 | | 25 | 29 | | 26 | 6 | | 27 | 9 | | 28 | 12 | | 29 | 30 | | 30 | 6 | | 31 | 18 | | 32 | 5 | | 33 | 25 | | 34 | 6 | | 35 | 11 | | 36 | 4 | | 37 | 7 | | 38 | 5 | | 39 | 26 | | 40 | 9 | | 41 | 8 | | 42 | 13 | | 43 | 22 | | 44 | 31 | | 45 | 4 | | 46 | 20 | | 47 | 2 | | 48 | 3 | | 49 | 18 |
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| 46.23% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.34306569343065696 | | totalSentences | 137 | | uniqueOpeners | 47 | |
| 92.59% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 72 | | matches | | 0 | "Instead, she says," | | 1 | "Instead, she reaches up and" |
| | ratio | 0.028 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 72 | | matches | | 0 | "He looks exactly the same," | | 1 | "he says, and there's that" | | 2 | "Her voice comes out sharper" | | 3 | "His amber eye — the" | | 4 | "She wants to tell him" | | 5 | "She wants to tell him" | | 6 | "She wants to tell him" | | 7 | "Her stomach drops." | | 8 | "She can't help it —" | | 9 | "She closes the door behind" | | 10 | "He kicks off his shoes" | | 11 | "She hates that she still" | | 12 | "he says, not looking at" | | 13 | "It's too clean, too professional." | | 14 | "She remembers the last time" | | 15 | "He turns, and for the" | | 16 | "She laughs, sharp and short" | | 17 | "She doesn't take it back." | | 18 | "He studies her for a" | | 19 | "He walks closer, close enough" |
| | ratio | 0.583 | |
| 50.28% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 72 | | matches | | 0 | "The door swings open before" | | 1 | "Lucien Moreau stands in the" | | 2 | "He looks exactly the same," | | 3 | "he says, and there's that" | | 4 | "Aurora replies, crossing her arms" | | 5 | "Her voice comes out sharper" | | 6 | "The door remains open behind" | | 7 | "His amber eye — the" | | 8 | "She wants to tell him" | | 9 | "She wants to tell him" | | 10 | "She wants to tell him" | | 11 | "The smile widens just a" | | 12 | "Her stomach drops." | | 13 | "Marius — the name alone" | | 14 | "Aurora steps back, letting him" | | 15 | "She can't help it —" | | 16 | "She closes the door behind" | | 17 | "The flat smells like cardamom" | | 18 | "He kicks off his shoes" | | 19 | "The words come out bitter," |
| | ratio | 0.819 | |
| 69.44% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 72 | | matches | | 0 | "Even when he was lying" |
| | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 1 | | matches | | 0 | "She watches him walk toward the bookshelf — the one stacked with ancient texts and forbidden knowledge — and wonders when she started collecting things that cou…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 1 | | matches | | 0 | "he says, not looking at her" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 3 | | fancyTags | | 0 | "She laughs (laugh)" | | 1 | "she repeats (repeat)" | | 2 | "the pages revealing (reveal)" |
| | dialogueSentences | 82 | | tagDensity | 0.134 | | leniency | 0.268 | | rawRatio | 0.273 | | effectiveRatio | 0.073 | |