| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 49 | | tagDensity | 0.469 | | leniency | 0.939 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1615 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "very" | | 2 | "slowly" |
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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) | |
| 90.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1615 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "measured" | | 1 | "weight" | | 2 | "aligned" |
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| 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 | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 77 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 100 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 77 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1628 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1123 | | uniqueNames | 18 | | maxNameDensity | 1.69 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Nia" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Rory | 19 | | Sichuan | 1 | | Silas | 5 | | Cardiff | 2 | | Llewellyn | 2 | | Land | 1 | | Law | 2 | | Thursday | 1 | | Nia | 19 | | November | 1 | | Eva | 1 | | Fairchild-Llewellyn | 1 | | Associate | 1 | | Family | 1 | | Child | 1 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Llewellyn" | | 5 | "Nia" | | 6 | "Eva" | | 7 | "Fairchild-Llewellyn" |
| | places | | 0 | "Sichuan" | | 1 | "Cardiff" | | 2 | "November" | | 3 | "London" |
| | globalScore | 0.654 | | windowScore | 0.5 | |
| 95.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 1 | | matches | | 0 | "as if putting it to sleep" |
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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 | 1628 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 100 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 36.18 | | std | 25.38 | | cv | 0.702 | | sampleLengths | | 0 | 83 | | 1 | 51 | | 2 | 12 | | 3 | 70 | | 4 | 31 | | 5 | 7 | | 6 | 43 | | 7 | 6 | | 8 | 43 | | 9 | 57 | | 10 | 54 | | 11 | 18 | | 12 | 46 | | 13 | 23 | | 14 | 35 | | 15 | 53 | | 16 | 6 | | 17 | 8 | | 18 | 18 | | 19 | 61 | | 20 | 18 | | 21 | 43 | | 22 | 7 | | 23 | 2 | | 24 | 79 | | 25 | 28 | | 26 | 33 | | 27 | 27 | | 28 | 48 | | 29 | 103 | | 30 | 16 | | 31 | 52 | | 32 | 28 | | 33 | 23 | | 34 | 42 | | 35 | 23 | | 36 | 4 | | 37 | 54 | | 38 | 22 | | 39 | 41 | | 40 | 21 | | 41 | 66 | | 42 | 15 | | 43 | 5 | | 44 | 103 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 77 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 182 | | matches | | 0 | "was re-lining" | | 1 | "was already memorising" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 4 | | flaggedSentences | 9 | | totalSentences | 100 | | ratio | 0.09 | | matches | | 0 | "Not the stillness of someone listening idly; the stillness of someone counting." | | 1 | "Rory felt it the way she felt a car drifting into her lane — a pressure before the shape of it registered." | | 2 | "\"Conference. Family law, two days of people explaining to each other what they already know.\" Nia's gaze moved over her — the courier bag still slung across her chest, the flat shoes, the hair loose and damp from the rain." | | 3 | "The two words sat between them with the whole of it behind them — the shouting through the floorboards that the neighbours had called about twice; the way Rory had learned to answer texts in a particular tone; the night in November when she had gone to Eva's with a suitcase and hadn't said goodbye to anyone who mattered." | | 4 | "She wasn't angry; that was worse." | | 5 | "A laugh escaped Rory before she could manage it — a real one, scraped up from somewhere low." | | 6 | "There was a difference, and Rory felt the whole weight of it — not the violence, which she had carried out of that city in a bag and set down somewhere private, but the smaller, heavier thing underneath: the months she had been quiet and competent and smiling while the person beside her redrew her daily, and how nobody who loved her had seen it, and how she had punished them for that by vanishing without a word." | | 7 | "Rory didn't flinch — she'd had years of practice not flinching — but her hand tightened on the glass, and Nia saw it, and Nia had always seen things." | | 8 | "He moved off toward the back, limping toward the bookshelf and the room behind it where the real conversations happened, and left her with the rain on the windows and the maps on the walls — London before the fire, Cardiff before the docks, all of it redrawn so many times you could barely tell what the original shape had been." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1122 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.030303030303030304 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.008021390374331552 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 100 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 100 | | mean | 16.28 | | std | 14.3 | | cv | 0.878 | | sampleLengths | | 0 | 43 | | 1 | 5 | | 2 | 3 | | 3 | 32 | | 4 | 5 | | 5 | 46 | | 6 | 12 | | 7 | 31 | | 8 | 32 | | 9 | 4 | | 10 | 3 | | 11 | 21 | | 12 | 10 | | 13 | 7 | | 14 | 9 | | 15 | 12 | | 16 | 22 | | 17 | 4 | | 18 | 2 | | 19 | 4 | | 20 | 39 | | 21 | 2 | | 22 | 6 | | 23 | 29 | | 24 | 20 | | 25 | 31 | | 26 | 11 | | 27 | 12 | | 28 | 11 | | 29 | 7 | | 30 | 40 | | 31 | 6 | | 32 | 20 | | 33 | 3 | | 34 | 19 | | 35 | 16 | | 36 | 17 | | 37 | 36 | | 38 | 6 | | 39 | 4 | | 40 | 4 | | 41 | 17 | | 42 | 1 | | 43 | 20 | | 44 | 41 | | 45 | 3 | | 46 | 15 | | 47 | 6 | | 48 | 17 | | 49 | 20 |
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| 66.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.44 | | totalSentences | 100 | | uniqueOpeners | 44 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 92.73% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 66 | | matches | | 0 | "Her wrists ached." | | 1 | "She wanted the bar stool" | | 2 | "He set the glass down," | | 3 | "She knew that voice." | | 4 | "It arrived several years late" | | 5 | "She was thinner in the" | | 6 | "She had changed, and she" | | 7 | "She took another drink" | | 8 | "It was not casual." | | 9 | "She looked up" | | 10 | "She wasn't angry; that was" | | 11 | "She was cool-headed." | | 12 | "She had always been cool-headed." | | 13 | "It was a gift and" | | 14 | "It came out flat and" | | 15 | "She reached into her coat" | | 16 | "She put it in her" | | 17 | "She went, and the bell" | | 18 | "He set the cloth down" | | 19 | "He looked at her with" |
| | ratio | 0.318 | |
| 20.61% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 66 | | matches | | 0 | "The green neon of The" | | 1 | "Her wrists ached." | | 2 | "She wanted the bar stool" | | 3 | "The Nest was nearly empty." | | 4 | "Rory sat two stools along" | | 5 | "Silas came out from the" | | 6 | "He set the glass down," | | 7 | "The woman on the next" | | 8 | "Rory felt it the way" | | 9 | "the woman said" | | 10 | "She knew that voice." | | 11 | "It arrived several years late" | | 12 | "Nia who had shared her" | | 13 | "Nia had worn a lot" | | 14 | "This Nia wore one ring," | | 15 | "She was thinner in the" | | 16 | "She had changed, and she" | | 17 | "Rory said, and smiled, and" | | 18 | "Nia's gaze moved over her" | | 19 | "Rory unbuckled the bag and" |
| | ratio | 0.879 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 27.65% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 5 | | matches | | 0 | "Two men hunched over a darts board, a couple in the corner sharing a bottle of red, and at the bar itself, a woman in a charcoal coat with her hair pinned up, t…" | | 1 | "Behind the bar, Silas was re-lining bottles with the unhurried precision of a man who had once had considerably more at stake, and he did not look at them, whic…" | | 2 | "The two words sat between them with the whole of it behind them — the shouting through the floorboards that the neighbours had called about twice; the way Rory …" | | 3 | "There was a difference, and Rory felt the whole weight of it — not the violence, which she had carried out of that city in a bag and set down somewhere private,…" | | 4 | "Nia hesitated at the edge of the stool, half-turned already toward the door, and the overhead lamp caught the fine new lines at her eyes that hadn't been there …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 49 | | tagDensity | 0.224 | | leniency | 0.449 | | rawRatio | 0.091 | | effectiveRatio | 0.041 | |