| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 46 | | tagDensity | 0.326 | | leniency | 0.652 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 73.57% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1135 | | totalAiIsmAdverbs | 6 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | adverb | "deliberately" | | count | 1 |
| | 5 | |
| | highlights | | 0 | "slowly" | | 1 | "suddenly" | | 2 | "quickly" | | 3 | "very" | | 4 | "deliberately" | | 5 | "really" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 82.38% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1135 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "warmth" | | 1 | "weight" | | 2 | "silk" | | 3 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 54 | | matches | (empty) | |
| 89.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 54 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 85 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 7 | | totalWords | 1144 | | ratio | 0.006 | | matches | | 0 | "xiǎo mèi" | | 1 | "You'll have it forever," | | 2 | "feeling" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 801 | | uniqueNames | 13 | | maxNameDensity | 2.62 | | worstName | "Tessa" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Tessa" | | discoveredNames | | Rory | 18 | | Silas | 6 | | Raven | 1 | | Nest | 2 | | November | 1 | | London | 1 | | Yu-Fei | 1 | | Tessa | 21 | | Fitzrovia | 1 | | Ellis | 1 | | Jennifer | 1 | | Cardiff | 1 | | Eva | 2 |
| | persons | | 0 | "Rory" | | 1 | "Silas" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Tessa" | | 5 | "Ellis" | | 6 | "Jennifer" | | 7 | "Eva" |
| | places | | 0 | "London" | | 1 | "Yu-Fei" | | 2 | "Fitzrovia" | | 3 | "Cardiff" |
| | globalScore | 0.189 | | windowScore | 0 | |
| 85.90% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | glossingSentenceCount | 1 | | matches | | 0 | "something between delight and apology" |
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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 | 1144 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 85 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 24.87 | | std | 24.79 | | cv | 0.997 | | sampleLengths | | 0 | 93 | | 1 | 29 | | 2 | 1 | | 3 | 49 | | 4 | 2 | | 5 | 69 | | 6 | 1 | | 7 | 56 | | 8 | 15 | | 9 | 57 | | 10 | 14 | | 11 | 2 | | 12 | 37 | | 13 | 52 | | 14 | 6 | | 15 | 36 | | 16 | 4 | | 17 | 4 | | 18 | 19 | | 19 | 40 | | 20 | 4 | | 21 | 8 | | 22 | 3 | | 23 | 4 | | 24 | 4 | | 25 | 39 | | 26 | 66 | | 27 | 15 | | 28 | 2 | | 29 | 3 | | 30 | 30 | | 31 | 3 | | 32 | 14 | | 33 | 94 | | 34 | 14 | | 35 | 6 | | 36 | 20 | | 37 | 31 | | 38 | 34 | | 39 | 3 | | 40 | 57 | | 41 | 25 | | 42 | 10 | | 43 | 5 | | 44 | 53 | | 45 | 11 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 54 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 135 | | matches | | |
| 42.02% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 85 | | ratio | 0.035 | | matches | | 0 | "The woman at the corner table was holding a glass of red wine and looking at her with an expression Rory couldn't immediately place — something between delight and apology." | | 1 | "\"Oh my God.\" Tessa set down the wine and stood, and there was a half-second of suspended uncertainty — embrace, handshake, nothing — before Tessa stepped around the table and hugged her." | | 2 | "Rory thought about the small economies of silence that had accumulated between them — unread messages, birthdays acknowledged then forgotten, a dinner twice postponed and then let quietly die." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 801 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.03495630461922597 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.012484394506866416 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 85 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 85 | | mean | 13.46 | | std | 11.66 | | cv | 0.866 | | sampleLengths | | 0 | 25 | | 1 | 23 | | 2 | 45 | | 3 | 29 | | 4 | 1 | | 5 | 8 | | 6 | 5 | | 7 | 5 | | 8 | 6 | | 9 | 15 | | 10 | 10 | | 11 | 2 | | 12 | 30 | | 13 | 27 | | 14 | 12 | | 15 | 1 | | 16 | 32 | | 17 | 8 | | 18 | 16 | | 19 | 8 | | 20 | 7 | | 21 | 13 | | 22 | 39 | | 23 | 5 | | 24 | 8 | | 25 | 6 | | 26 | 2 | | 27 | 15 | | 28 | 22 | | 29 | 1 | | 30 | 20 | | 31 | 31 | | 32 | 6 | | 33 | 24 | | 34 | 12 | | 35 | 4 | | 36 | 4 | | 37 | 5 | | 38 | 7 | | 39 | 7 | | 40 | 12 | | 41 | 28 | | 42 | 4 | | 43 | 8 | | 44 | 3 | | 45 | 4 | | 46 | 4 | | 47 | 19 | | 48 | 20 | | 49 | 6 |
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| 69.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.47058823529411764 | | totalSentences | 85 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 48 | | matches | | 0 | "Even her mother, on the" | | 1 | "Then Tessa said," |
| | ratio | 0.042 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 48 | | matches | | 0 | "She pushed through into the" | | 1 | "She was halfway to the" | | 2 | "It was the full name" | | 3 | "She was blonde now, a" | | 4 | "She smelled expensive, something with" | | 5 | "She was conscious, suddenly, of" | | 6 | "It came out too quickly," | | 7 | "He had shaken her hand" | | 8 | "They smiled at each other." | | 9 | "*You'll have it forever,* Tessa" | | 10 | "She thought about how, in" | | 11 | "She had not been able" | | 12 | "She had barely been able" | | 13 | "She nodded toward the back" |
| | ratio | 0.292 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 40 | | totalSentences | 48 | | matches | | 0 | "The green neon above the" | | 1 | "She pushed through into the" | | 2 | "Tuesday nights at the Nest" | | 3 | "She was halfway to the" | | 4 | "It was the full name" | | 5 | "Nobody in London used it." | | 6 | "Aurora belonged to a different" | | 7 | "The woman at the corner" | | 8 | "She was blonde now, a" | | 9 | "Rory had to run her" | | 10 | "Tessa set down the wine" | | 11 | "She smelled expensive, something with" | | 12 | "Tessa gestured at the opposite" | | 13 | "Rory sat, setting the empty" | | 14 | "She was conscious, suddenly, of" | | 15 | "Tessa laughed, a short bright" | | 16 | "It came out too quickly," | | 17 | "Rory had seen him exactly" | | 18 | "He had shaken her hand" | | 19 | "Tessa turned the wine glass" |
| | ratio | 0.833 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 48 | | matches | | 0 | "To Silas she was Rory." | | 1 | "To Yu-Fei she was *xiǎo" |
| | ratio | 0.042 | |
| 18.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 4 | | matches | | 0 | "She was blonde now, a warm honey color that caught the low lamplight, and she wore a camel coat over a silk blouse the color of bone." | | 1 | "Rory did not look toward the bar, where Silas had appeared in her peripheral vision and was now, very deliberately, polishing a glass that did not need polishin…" | | 2 | "Rory thought about the small economies of silence that had accumulated between them — unread messages, birthdays acknowledged then forgotten, a dinner twice pos…" | | 3 | "Rory signaled Silas, two fingers raised, and he tilted his head in acknowledgment and reached for the good whisky, the one he kept for her on nights she came ho…" |
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| 91.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 46 | | tagDensity | 0.152 | | leniency | 0.304 | | rawRatio | 0.143 | | effectiveRatio | 0.043 | |