| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 27 | | adverbTagCount | 1 | | adverbTags | | 0 | "Nia said quietly [quietly]" |
| | dialogueSentences | 66 | | tagDensity | 0.409 | | leniency | 0.818 | | rawRatio | 0.037 | | effectiveRatio | 0.03 | |
| 73.03% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1483 | | totalAiIsmAdverbs | 8 | | found | | | highlights | | 0 | "gently" | | 1 | "very" | | 2 | "precisely" | | 3 | "perfectly" |
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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) | |
| 89.89% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1483 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "sense of" | | 1 | "absolutely" | | 2 | "silence" |
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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 | 65 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 65 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 103 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 65 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 2 | | totalWords | 1494 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 957 | | uniqueNames | 11 | | maxNameDensity | 2.3 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 22 | | Nest | 1 | | Cardiff | 1 | | Nia | 13 | | Silas | 5 | | Fifty-eight | 1 | | Spar | 1 | | Wellfield | 1 | | Road | 1 | | Newport | 1 | | Evan | 1 |
| | persons | | 0 | "Rory" | | 1 | "Nia" | | 2 | "Silas" | | 3 | "Evan" |
| | places | | 0 | "Cardiff" | | 1 | "Spar" | | 2 | "Wellfield" | | 3 | "Road" | | 4 | "Newport" |
| | globalScore | 0.351 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.669 | | wordCount | 1494 | | matches | | 0 | "not recognition first but the body's odd chemical alarm, the sense of being looked at" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 103 | | matches | | 0 | "noticed that the" | | 1 | "heard that phrase" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 25.32 | | std | 26.12 | | cv | 1.032 | | sampleLengths | | 0 | 91 | | 1 | 14 | | 2 | 47 | | 3 | 2 | | 4 | 36 | | 5 | 32 | | 6 | 70 | | 7 | 4 | | 8 | 23 | | 9 | 1 | | 10 | 1 | | 11 | 7 | | 12 | 21 | | 13 | 40 | | 14 | 27 | | 15 | 55 | | 16 | 3 | | 17 | 23 | | 18 | 3 | | 19 | 2 | | 20 | 105 | | 21 | 4 | | 22 | 6 | | 23 | 2 | | 24 | 53 | | 25 | 25 | | 26 | 40 | | 27 | 5 | | 28 | 57 | | 29 | 25 | | 30 | 6 | | 31 | 9 | | 32 | 1 | | 33 | 85 | | 34 | 8 | | 35 | 1 | | 36 | 6 | | 37 | 4 | | 38 | 77 | | 39 | 2 | | 40 | 53 | | 41 | 24 | | 42 | 18 | | 43 | 5 | | 44 | 66 | | 45 | 14 | | 46 | 29 | | 47 | 10 | | 48 | 48 | | 49 | 1 |
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| 94.47% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 65 | | matches | | 0 | "being looked" | | 1 | "being asked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 153 | | matches | | |
| 4.16% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 103 | | ratio | 0.049 | | matches | | 0 | "The rain had got into everything by the time Rory pushed through the door of the Nest — into the collar of her jacket, the cuffs, the laces of her boots, the paper bag of receipts she should have handed in three hours ago." | | 1 | "It happened the way those things do — not recognition first but the body's odd chemical alarm, the sense of being looked at from an angle no stranger should have." | | 2 | "Nobody had called her that since Cardiff, since her mother's voice up the stairs on school mornings, since —" | | 3 | "Because there it was — *my mam* — and the last time Rory had heard that phrase in that voice was over the phone in a stairwell in a flat in Newport, with Evan in the next room and the television too loud, and Nia crying so hard Rory could not make out the hospital's name." | | 4 | "\"I was corroborating.\" And there it came — the smile, the real one, crooked and quick and entirely fifteen — and then it folded itself away like a letter being put back in a drawer, and the charcoal suit sat up straight again." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 956 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.034518828451882845 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.014644351464435146 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 103 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 103 | | mean | 14.5 | | std | 14.13 | | cv | 0.974 | | sampleLengths | | 0 | 44 | | 1 | 17 | | 2 | 30 | | 3 | 14 | | 4 | 25 | | 5 | 22 | | 6 | 2 | | 7 | 36 | | 8 | 30 | | 9 | 2 | | 10 | 19 | | 11 | 3 | | 12 | 4 | | 13 | 28 | | 14 | 7 | | 15 | 9 | | 16 | 4 | | 17 | 4 | | 18 | 19 | | 19 | 1 | | 20 | 1 | | 21 | 5 | | 22 | 2 | | 23 | 16 | | 24 | 5 | | 25 | 37 | | 26 | 3 | | 27 | 17 | | 28 | 10 | | 29 | 46 | | 30 | 9 | | 31 | 3 | | 32 | 21 | | 33 | 2 | | 34 | 3 | | 35 | 2 | | 36 | 9 | | 37 | 9 | | 38 | 21 | | 39 | 41 | | 40 | 25 | | 41 | 4 | | 42 | 6 | | 43 | 2 | | 44 | 23 | | 45 | 20 | | 46 | 10 | | 47 | 22 | | 48 | 3 | | 49 | 25 |
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| 51.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3786407766990291 | | totalSentences | 103 | | uniqueOpeners | 39 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 57 | | matches | | 0 | "She peeled the hi-vis off" | | 1 | "She climbed onto the third" | | 2 | "It happened the way those" | | 3 | "Her face was thinner than" | | 4 | "She'd been the one who" | | 5 | "she gestured at Rory's face," | | 6 | "She said it flatly, without" | | 7 | "Her hand was perfectly steady." | | 8 | "She said it almost gently" | | 9 | "She stood, and slid the" | | 10 | "She pulled her coat on," | | 11 | "She went out into the" | | 12 | "She sat with the glass" |
| | ratio | 0.228 | |
| 38.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 48 | | totalSentences | 57 | | matches | | 0 | "The rain had got into" | | 1 | "The green neon over the" | | 2 | "Silas said, without looking up" | | 3 | "She peeled the hi-vis off" | | 4 | "She climbed onto the third" | | 5 | "It happened the way those" | | 6 | "The woman was in a" | | 7 | "Hair pinned up." | | 8 | "A slim gold watch." | | 9 | "A glass of red she" | | 10 | "Her face was thinner than" | | 11 | "Everything about her was thinner" | | 12 | "the woman said" | | 13 | "Nobody called her that." | | 14 | "Nobody had called her that" | | 15 | "Rory laughed, one syllable, disbelieving." | | 16 | "Nia's mouth did something that" | | 17 | "Rory looked at her, the" | | 18 | "Nia turned the stem of" | | 19 | "Silas set a glass of" |
| | ratio | 0.842 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 57 | | matches | | 0 | "Now she sat with her" | | 1 | "Because there it was —" | | 2 | "To the scar." |
| | ratio | 0.053 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 18 | | technicalSentenceCount | 1 | | matches | | 0 | "The woman was in a charcoal suit that fitted her the way suits fit people who have them fitted." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 27 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 2 | | fancyTags | | 0 | "Silas set (silas set)" | | 1 | "Rory heard (hear)" |
| | dialogueSentences | 66 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0.167 | | effectiveRatio | 0.061 | |