| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 40 | | adverbTagCount | 1 | | adverbTags | | 0 | "Nia said slowly [slowly]" |
| | dialogueSentences | 114 | | tagDensity | 0.351 | | leniency | 0.702 | | rawRatio | 0.025 | | effectiveRatio | 0.018 | |
| 86.90% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2290 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slowly" | | 1 | "slightly" | | 2 | "utterly" | | 3 | "really" | | 4 | "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) | |
| 71.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2290 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "silence" | | 1 | "silk" | | 2 | "flickered" | | 3 | "unspoken" | | 4 | "measured" | | 5 | "weight" | | 6 | "traced" | | 7 | "constructed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 186 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 186 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 258 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 49 | | totalWords | 2290 | | ratio | 0.021 | | matches | | 0 | "I have a pension plan now" | | 1 | "Nia Bowen. Senior Product Manager. Synaptic Solutions." | | 2 | "That's not your name. I've known you since we were eleven. You don't get to rewrite that." | | 3 | "Sorry I was too busy surviving to consider the emotional collateral damage?" | | 4 | "Five more minutes." | | 5 | "I need a moment." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 114 | | wordCount | 1598 | | uniqueNames | 22 | | maxNameDensity | 2.94 | | worstName | "Nia" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Nia" | | discoveredNames | | Chapter | 1 | | Raven | 2 | | Nest | 2 | | Rory | 35 | | Cardiff | 2 | | London | 2 | | Years | 1 | | Nia | 47 | | Old | 1 | | Bowen | 1 | | Product | 2 | | Manager | 2 | | Three | 2 | | English | 1 | | Silas | 5 | | January | 1 | | Careful | 1 | | New | 1 | | Year | 1 | | Eve | 1 | | Senior | 2 | | Observational | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Nia" | | 4 | "Old" | | 5 | "Bowen" | | 6 | "Manager" | | 7 | "Silas" | | 8 | "Year" |
| | places | | 0 | "Cardiff" | | 1 | "London" | | 2 | "Three" | | 3 | "English" |
| | globalScore | 0.029 | | windowScore | 0 | |
| 59.91% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 111 | | glossingSentenceCount | 4 | | matches | | 0 | "looked like someone's reliable solicitor" | | 1 | "as if cataloguing the flavour notes for later discussion" | | 2 | "quite mastered" | | 3 | "appeared, leaning against the frame with his silver signet ring catching the light" |
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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 | 2290 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 258 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 119 | | mean | 19.24 | | std | 19.28 | | cv | 1.002 | | sampleLengths | | 0 | 6 | | 1 | 9 | | 2 | 43 | | 3 | 85 | | 4 | 20 | | 5 | 35 | | 6 | 1 | | 7 | 29 | | 8 | 13 | | 9 | 45 | | 10 | 18 | | 11 | 2 | | 12 | 3 | | 13 | 60 | | 14 | 11 | | 15 | 27 | | 16 | 13 | | 17 | 33 | | 18 | 23 | | 19 | 4 | | 20 | 6 | | 21 | 2 | | 22 | 6 | | 23 | 13 | | 24 | 31 | | 25 | 8 | | 26 | 44 | | 27 | 20 | | 28 | 24 | | 29 | 40 | | 30 | 4 | | 31 | 1 | | 32 | 5 | | 33 | 4 | | 34 | 36 | | 35 | 6 | | 36 | 3 | | 37 | 17 | | 38 | 1 | | 39 | 41 | | 40 | 2 | | 41 | 31 | | 42 | 38 | | 43 | 9 | | 44 | 8 | | 45 | 14 | | 46 | 57 | | 47 | 4 | | 48 | 2 | | 49 | 2 |
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| 99.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 186 | | matches | | 0 | "was absorbed" | | 1 | "being asked" | | 2 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 292 | | matches | | 0 | "was drying" | | 1 | "was laughing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 258 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1604 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 53 | | adverbRatio | 0.033042394014962596 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.006234413965087282 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 258 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 258 | | mean | 8.88 | | std | 7.51 | | cv | 0.846 | | sampleLengths | | 0 | 15 | | 1 | 33 | | 2 | 10 | | 3 | 11 | | 4 | 12 | | 5 | 7 | | 6 | 1 | | 7 | 26 | | 8 | 28 | | 9 | 4 | | 10 | 16 | | 11 | 5 | | 12 | 15 | | 13 | 5 | | 14 | 10 | | 15 | 1 | | 16 | 6 | | 17 | 13 | | 18 | 10 | | 19 | 6 | | 20 | 3 | | 21 | 4 | | 22 | 8 | | 23 | 2 | | 24 | 3 | | 25 | 22 | | 26 | 10 | | 27 | 7 | | 28 | 11 | | 29 | 2 | | 30 | 3 | | 31 | 13 | | 32 | 7 | | 33 | 17 | | 34 | 15 | | 35 | 8 | | 36 | 6 | | 37 | 5 | | 38 | 8 | | 39 | 2 | | 40 | 7 | | 41 | 10 | | 42 | 7 | | 43 | 6 | | 44 | 24 | | 45 | 9 | | 46 | 5 | | 47 | 2 | | 48 | 3 | | 49 | 5 |
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| 52.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 24 | | diversityRatio | 0.37209302325581395 | | totalSentences | 258 | | uniqueOpeners | 96 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 156 | | matches | | 0 | "Then the laugh stopped." | | 1 | "Then she smiled, and the" | | 2 | "Really still, the way animals" | | 3 | "Instead, Nia picked up her" | | 4 | "Then she was gone." |
| | ratio | 0.032 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 156 | | matches | | 0 | "It cut through the low" | | 1 | "She gripped the glass she" | | 2 | "She was laughing at something" | | 3 | "She kept her voice level" | | 4 | "She looked like someone's reliable" | | 5 | "She looked like a stranger." | | 6 | "Their fingers almost touched." | | 7 | "She didn't usually drink on" | | 8 | "Her jaw worked, and Rory" | | 9 | "They blurred together like colours" | | 10 | "I've known you since we" | | 11 | "You don't get to rewrite" | | 12 | "It sounded wrong in Nia's" | | 13 | "She stopped herself." | | 14 | "She rubbed it without thinking." | | 15 | "She laughed, but there was" | | 16 | "She opened her mouth, but" | | 17 | "*I need a moment.*" | | 18 | "She traced a pattern on" | | 19 | "She gestured at herself" |
| | ratio | 0.199 | |
| 49.74% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 128 | | totalSentences | 156 | | matches | | 0 | "# Chapter 7: The Raven's" | | 1 | "It cut through the low" | | 2 | "She gripped the glass she" | | 3 | "Nia stood by the entrance," | | 4 | "The kind of coat that" | | 5 | "The dark curls were shorter," | | 6 | "She was laughing at something" | | 7 | "Nia's gaze swept the bar" | | 8 | "The bar's usual soundtrack of" | | 9 | "Rory set the glass down." | | 10 | "The cloth she'd been using" | | 11 | "Nobody in London called her" | | 12 | "The name belonged to a" | | 13 | "Rory felt it land in" | | 14 | "She kept her voice level" | | 15 | "Years of practice." | | 16 | "Nia crossed the room in" | | 17 | "That was new." | | 18 | "The Nia Rory remembered drifted" | | 19 | "This woman walked like she" |
| | ratio | 0.821 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 156 | | matches | (empty) | | ratio | 0 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 7 | | matches | | 0 | "The dark curls were shorter, sculpted into something architectural, and fine lines fanned from the corners of her eyes that hadn't been there three years ago." | | 1 | "She was laughing at something the woman beside her had said, her head thrown back, her teeth catching the green glow of the neon sign above the door." | | 2 | "The Nia Rory remembered drifted through spaces like smoke, arriving at destinations sideways, as if commitment to a single direction frightened her." | | 3 | "A measured sip followed by a pause, as if cataloguing the flavour notes for later discussion." | | 4 | "The kind that has weight and texture, the kind you can feel pressing against your eardrums." | | 5 | "The door closed behind her, and the green neon sign flickered once, as if it had absorbed something heavy from the room." | | 6 | "The way a man who'd spent decades reading people on four continents asked a question he already knew the answer to." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 40 | | uselessAdditionCount | 1 | | matches | | 0 | "Nia said, as if she'd heard every unspoken word" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 3 | | fancyTags | | 0 | "Rory repeated (repeat)" | | 1 | "She laughed (laugh)" | | 2 | "Silas added (add)" |
| | dialogueSentences | 114 | | tagDensity | 0.14 | | leniency | 0.281 | | rawRatio | 0.188 | | effectiveRatio | 0.053 | |