| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "Niamh looked around [around]" | | 1 | "Niamh said finally [finally]" |
| | dialogueSentences | 51 | | tagDensity | 0.255 | | leniency | 0.51 | | rawRatio | 0.154 | | effectiveRatio | 0.078 | |
| 95.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1072 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 86.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1072 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "lilt" | | 1 | "silence" | | 2 | "weight" |
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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 | 57 | | matches | (empty) | |
| 92.73% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 57 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1078 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 765 | | uniqueNames | 9 | | maxNameDensity | 2.75 | | worstName | "Niamh" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Niamh" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Tuesday | 1 | | Silas | 2 | | Aurora | 14 | | Cardiff | 1 | | Cork | 1 | | Niamh | 21 | | Roath | 1 |
| | persons | | 0 | "Nest" | | 1 | "Silas" | | 2 | "Aurora" | | 3 | "Niamh" |
| | places | | 0 | "Raven" | | 1 | "Cardiff" | | 2 | "Cork" | | 3 | "Roath" |
| | globalScore | 0.127 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | 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 | 1078 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 18.59 | | std | 20.94 | | cv | 1.127 | | sampleLengths | | 0 | 90 | | 1 | 1 | | 2 | 25 | | 3 | 2 | | 4 | 88 | | 5 | 31 | | 6 | 49 | | 7 | 5 | | 8 | 1 | | 9 | 6 | | 10 | 22 | | 11 | 36 | | 12 | 3 | | 13 | 2 | | 14 | 6 | | 15 | 7 | | 16 | 19 | | 17 | 57 | | 18 | 8 | | 19 | 42 | | 20 | 4 | | 21 | 1 | | 22 | 7 | | 23 | 57 | | 24 | 14 | | 25 | 4 | | 26 | 3 | | 27 | 11 | | 28 | 25 | | 29 | 3 | | 30 | 3 | | 31 | 1 | | 32 | 54 | | 33 | 8 | | 34 | 4 | | 35 | 24 | | 36 | 2 | | 37 | 6 | | 38 | 5 | | 39 | 37 | | 40 | 38 | | 41 | 5 | | 42 | 6 | | 43 | 42 | | 44 | 7 | | 45 | 25 | | 46 | 14 | | 47 | 1 | | 48 | 7 | | 49 | 4 |
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| 80.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 57 | | matches | | 0 | "been mistaken" | | 1 | "was cropped" | | 2 | "been assembled" | | 3 | "being asked" |
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| 56.12% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 139 | | matches | | 0 | "was seeing" | | 1 | "was not waiting" | | 2 | "was simply absorbing" |
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| 22.56% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 95 | | ratio | 0.042 | | matches | | 0 | "What she didn't expect was the woman at the end of the bar, a glass of red wine held to her lips like a question mark, and the way her own name — her old one — caught in the back of her throat." | | 1 | "\"Sit down before I lose my nerve,\" Niamh said, and her voice at least was the same — that low Cork lilt she used to put on thicker after a drink." | | 2 | "Silas caught her eye from behind the bar, a slight tilt of his head — the old question, are you alright?" | | 3 | "She thought of the last time she'd seen Niamh — a kitchen in Roath, three a.m., a kettle whistling, Niamh saying, you're better than him, Aurora, please, please — and she thought of how she had said yes, I know, and gone back anyway." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 486 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.02263374485596708 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.00411522633744856 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 11.35 | | std | 9.75 | | cv | 0.859 | | sampleLengths | | 0 | 18 | | 1 | 28 | | 2 | 44 | | 3 | 1 | | 4 | 3 | | 5 | 15 | | 6 | 7 | | 7 | 2 | | 8 | 16 | | 9 | 33 | | 10 | 27 | | 11 | 5 | | 12 | 7 | | 13 | 31 | | 14 | 2 | | 15 | 21 | | 16 | 6 | | 17 | 20 | | 18 | 5 | | 19 | 1 | | 20 | 6 | | 21 | 14 | | 22 | 8 | | 23 | 26 | | 24 | 10 | | 25 | 3 | | 26 | 2 | | 27 | 6 | | 28 | 7 | | 29 | 13 | | 30 | 6 | | 31 | 3 | | 32 | 10 | | 33 | 44 | | 34 | 8 | | 35 | 38 | | 36 | 4 | | 37 | 4 | | 38 | 1 | | 39 | 7 | | 40 | 7 | | 41 | 10 | | 42 | 10 | | 43 | 9 | | 44 | 21 | | 45 | 10 | | 46 | 4 | | 47 | 4 | | 48 | 3 | | 49 | 11 |
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| 44.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3263157894736842 | | totalSentences | 95 | | uniqueOpeners | 31 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 50 | | matches | | 0 | "Then recognition moved through her" | | 1 | "Then the laugh trailed off" |
| | ratio | 0.04 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 50 | | matches | | 0 | "Her hair was cropped, precise." | | 1 | "She looked as though she'd" | | 2 | "She gave him a small" | | 3 | "He poured her a whisky" | | 4 | "She thought of the last" | | 5 | "She thought she would have" | | 6 | "She wasn't thirty yet and" | | 7 | "She had stopped covering it" | | 8 | "she said, in the tone" | | 9 | "She thought of the nights" | | 10 | "She thought of Niamh saying," | | 11 | "It came out smaller than" | | 12 | "She lifted her glass." |
| | ratio | 0.26 | |
| 30.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 43 | | totalSentences | 50 | | matches | | 0 | "The green neon outside The" | | 1 | "Aurora shook water from her" | | 2 | "The woman turned." | | 3 | "Aurora crossed the room slowly," | | 4 | "Niamh O'Connell had worn her" | | 5 | "The woman at the bar" | | 6 | "Her hair was cropped, precise." | | 7 | "She looked as though she'd" | | 8 | "Niamh said, and her voice" | | 9 | "Silas caught her eye from" | | 10 | "She gave him a small" | | 11 | "He poured her a whisky" | | 12 | "Aurora took the whisky" | | 13 | "Niamh laughed, and for a" | | 14 | "Niamh turned the wine glass" | | 15 | "Aurora didn't answer." | | 16 | "She thought of the last" | | 17 | "Niamh looked around, at the" | | 18 | "Niamh's eyes moved over her," | | 19 | "Aurora felt it, the practised" |
| | ratio | 0.86 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 93.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 2 | | matches | | 0 | "Niamh O'Connell had worn her hair down to her waist in Cardiff, had lived in oversized jumpers that smelled of her flatmate's cigarettes, had argued contract la…" | | 1 | "The woman at the bar wore a blazer the colour of dried blood and a watch that caught the lamplight like something expensive wanting to be noticed." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.176 | | leniency | 0.353 | | rawRatio | 0 | | effectiveRatio | 0 | |