| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "Meg said finally [finally]" | | 1 | "she gestured vaguely [vaguely]" |
| | dialogueSentences | 56 | | tagDensity | 0.232 | | leniency | 0.464 | | rawRatio | 0.154 | | effectiveRatio | 0.071 | |
| 83.59% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1219 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "really" | | 1 | "very" | | 2 | "carefully" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 91.80% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1219 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 56 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 56 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 71 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1232 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 848 | | uniqueNames | 4 | | maxNameDensity | 2 | | worstName | "Meg" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Rory" | | discoveredNames | | | persons | | | places | | | globalScore | 0.498 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 38 | | 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 | 1232 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 20.88 | | std | 26.28 | | cv | 1.259 | | sampleLengths | | 0 | 73 | | 1 | 59 | | 2 | 6 | | 3 | 4 | | 4 | 72 | | 5 | 1 | | 6 | 46 | | 7 | 4 | | 8 | 4 | | 9 | 86 | | 10 | 6 | | 11 | 1 | | 12 | 6 | | 13 | 4 | | 14 | 53 | | 15 | 6 | | 16 | 3 | | 17 | 9 | | 18 | 5 | | 19 | 18 | | 20 | 3 | | 21 | 12 | | 22 | 8 | | 23 | 60 | | 24 | 5 | | 25 | 4 | | 26 | 1 | | 27 | 5 | | 28 | 1 | | 29 | 100 | | 30 | 13 | | 31 | 1 | | 32 | 2 | | 33 | 2 | | 34 | 56 | | 35 | 11 | | 36 | 4 | | 37 | 12 | | 38 | 20 | | 39 | 2 | | 40 | 16 | | 41 | 2 | | 42 | 91 | | 43 | 31 | | 44 | 5 | | 45 | 3 | | 46 | 3 | | 47 | 52 | | 48 | 59 | | 49 | 11 |
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| 99.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 56 | | matches | | |
| 67.55% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 151 | | matches | | 0 | "was peeling" | | 1 | "were updating" | | 2 | "was seeing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 98 | | ratio | 0.071 | | matches | | 0 | "She'd wanted the kind of drink that went down like a lie — something sweet, something that let you pretend." | | 1 | "Then the scarf came off, and the face underneath arranged itself into something familiar — the long nose, the gap in the front teeth, the eyes that always looked as if they'd just finished laughing at a joke no one else had heard." | | 2 | "There was a pause in which Meg looked at her, really looked — the kind of look old friends gave you when they were updating the file." | | 3 | "Meg laughed, and that, at least, was the laugh Rory remembered — a rough bark of a thing, too loud for the room." | | 4 | "The bar hummed around them — someone laughing in the booth by the window, the clatter of ice in a shaker, the low thrum of whatever Silas had put on the speakers, something with a piano in it and a woman singing in French." | | 5 | "Then she reached out and, with a gentleness Rory had almost forgotten the shape of, touched the inside of her wrist — the small crescent scar there, pale as a fingernail paring, the one she'd got falling off a wall when she was eight years old and Meg hadn't even known her yet." | | 6 | "Rory looked down at the whisky, at her own reflection shivering in the surface of it — a woman with short dark hair and a mouth that had forgotten, somewhere along the way, how to tremble." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 843 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.03795966785290629 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0071174377224199285 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 12.57 | | std | 13.55 | | cv | 1.077 | | sampleLengths | | 0 | 24 | | 1 | 4 | | 2 | 20 | | 3 | 25 | | 4 | 6 | | 5 | 4 | | 6 | 29 | | 7 | 20 | | 8 | 6 | | 9 | 4 | | 10 | 29 | | 11 | 43 | | 12 | 1 | | 13 | 25 | | 14 | 21 | | 15 | 4 | | 16 | 4 | | 17 | 27 | | 18 | 4 | | 19 | 6 | | 20 | 21 | | 21 | 9 | | 22 | 19 | | 23 | 6 | | 24 | 1 | | 25 | 6 | | 26 | 4 | | 27 | 23 | | 28 | 13 | | 29 | 11 | | 30 | 6 | | 31 | 6 | | 32 | 3 | | 33 | 9 | | 34 | 5 | | 35 | 15 | | 36 | 3 | | 37 | 3 | | 38 | 12 | | 39 | 5 | | 40 | 3 | | 41 | 24 | | 42 | 36 | | 43 | 5 | | 44 | 4 | | 45 | 1 | | 46 | 5 | | 47 | 1 | | 48 | 7 | | 49 | 31 |
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| 62.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.41836734693877553 | | totalSentences | 98 | | uniqueOpeners | 41 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 49 | | matches | | 0 | "Then the scarf came off," | | 1 | "Then she reached out and," |
| | ratio | 0.041 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 49 | | matches | | 0 | "She hadn't wanted whisky." | | 1 | "She'd wanted the kind of" | | 2 | "She didn't look up." | | 3 | "She lifted her head." | | 4 | "She knew what Meg was" | | 5 | "He went back to his" | | 6 | "She had been Rory's flatmate" | | 7 | "They hadn't spoken properly after" | | 8 | "She thought about it." | | 9 | "she gestured vaguely at her" | | 10 | "She had meant to say" | | 11 | "Her voice caught on something" |
| | ratio | 0.245 | |
| 41.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 49 | | matches | | 0 | "The green neon bled through" | | 1 | "She hadn't wanted whisky." | | 2 | "She'd wanted the kind of" | | 3 | "The bell above the door" | | 4 | "She didn't look up." | | 5 | "People came in from the" | | 6 | "That was one of the" | | 7 | "She lifted her head." | | 8 | "The woman in the doorway" | | 9 | "Meg crossed the floor and" | | 10 | "Rory kept very still." | | 11 | "She knew what Meg was" | | 12 | "The hair was shorter now," | | 13 | "The fringe she used to" | | 14 | "Meg said finally" | | 15 | "Meg laughed, and that, at" | | 16 | "Silas, wiping a glass at" | | 17 | "Rory shook her head at" | | 18 | "He went back to his" | | 19 | "Meg turned on her stool" |
| | ratio | 0.837 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 49.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 3 | | matches | | 0 | "She'd wanted the kind of drink that went down like a lie — something sweet, something that let you pretend." | | 1 | "Then the scarf came off, and the face underneath arranged itself into something familiar — the long nose, the gap in the front teeth, the eyes that always looke…" | | 2 | "Rory looked down at the whisky, at her own reflection shivering in the surface of it — a woman with short dark hair and a mouth that had forgotten, somewhere al…" |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "the drink came, without looking at Rory," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 56 | | tagDensity | 0.179 | | leniency | 0.357 | | rawRatio | 0.1 | | effectiveRatio | 0.036 | |