| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.34 | | leniency | 0.68 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.70% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1328 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "really" | | 2 | "very" |
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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) | |
| 96.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1328 | | totalAiIsms | 1 | | 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 | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 67 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 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 | 62 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 8 | | markdownWords | 22 | | totalWords | 1349 | | ratio | 0.016 | | matches | | 0 | "is" | | 1 | "doing" | | 2 | "Three years." | | 3 | "here if you need me" | | 4 | "you don't want the details," | | 5 | "for now" | | 6 | "I told you" | | 7 | "I told you," |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 1003 | | uniqueNames | 12 | | maxNameDensity | 2.09 | | worstName | "Niamh" | | maxWindowNameDensity | 4 | | worstWindowName | "Niamh" | | discoveredNames | | Aurora | 17 | | Silas | 5 | | Golden | 1 | | Empress | 1 | | Wednesdays | 1 | | Raven | 2 | | Nest | 2 | | Soho | 2 | | Doherty | 1 | | Niamh | 21 | | Cardiff | 2 | | Penarth | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Silas" | | 2 | "Empress" | | 3 | "Raven" | | 4 | "Doherty" | | 5 | "Niamh" |
| | places | | 0 | "Golden" | | 1 | "Soho" | | 2 | "Cardiff" | | 3 | "Penarth" |
| | globalScore | 0.453 | | windowScore | 0.333 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 3 | | matches | | 0 | "smelled like rain and a perfume Aurora did" | | 1 | "as if testing whether the old laugh still fit between them" | | 2 | "not quite change" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.741 | | wordCount | 1349 | | matches | | 0 | "not long, but furnished" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 100 | | matches | | 0 | "thinking that the" | | 1 | "was that it" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 26.98 | | std | 32.83 | | cv | 1.217 | | sampleLengths | | 0 | 85 | | 1 | 112 | | 2 | 4 | | 3 | 72 | | 4 | 1 | | 5 | 55 | | 6 | 6 | | 7 | 62 | | 8 | 39 | | 9 | 2 | | 10 | 10 | | 11 | 2 | | 12 | 4 | | 13 | 6 | | 14 | 77 | | 15 | 4 | | 16 | 2 | | 17 | 6 | | 18 | 4 | | 19 | 26 | | 20 | 1 | | 21 | 1 | | 22 | 106 | | 23 | 11 | | 24 | 42 | | 25 | 3 | | 26 | 21 | | 27 | 4 | | 28 | 27 | | 29 | 82 | | 30 | 12 | | 31 | 2 | | 32 | 3 | | 33 | 2 | | 34 | 80 | | 35 | 5 | | 36 | 4 | | 37 | 9 | | 38 | 80 | | 39 | 7 | | 40 | 8 | | 41 | 42 | | 42 | 18 | | 43 | 3 | | 44 | 4 | | 45 | 103 | | 46 | 15 | | 47 | 50 | | 48 | 7 | | 49 | 18 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 167 | | matches | | 0 | "was only stopping" | | 1 | "was reaching" | | 2 | "was wearing" | | 3 | "was only seeing" | | 4 | "was looking" | | 5 | "was thinking" | | 6 | "was already reaching" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 4 | | flaggedSentences | 6 | | totalSentences | 100 | | ratio | 0.06 | | matches | | 0 | "\"Rory Carter.\" Niamh laughed, short and disbelieving, and crossed the room the way she had always crossed rooms — as if the floor owed her something." | | 1 | "Up close she was not too adult at all; she was exactly their age, twenty-five, only she had spent those years forward instead of sideways." | | 2 | "His limp, Aurora noticed, was worse tonight; the weather, probably." | | 3 | "He caught Aurora's eye, gave her half a nod — *here if you need me* — and drifted away to the other end of the bar." | | 4 | "All those afternoons in the Cardiff library; all those unread letters; Niamh crying into a tea towel on a garden wall in 2003." | | 5 | "Something in her face eased, not into forgiveness — it was not that simple, and they both knew it was not that simple — but into a kind of truce with the fact of the room, and the rain, and the years." |
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| 96.69% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1005 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 44 | | adverbRatio | 0.04378109452736319 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.012935323383084577 | |
| 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 | 13.49 | | std | 13.92 | | cv | 1.032 | | sampleLengths | | 0 | 30 | | 1 | 9 | | 2 | 46 | | 3 | 58 | | 4 | 11 | | 5 | 43 | | 6 | 4 | | 7 | 7 | | 8 | 7 | | 9 | 33 | | 10 | 25 | | 11 | 1 | | 12 | 26 | | 13 | 19 | | 14 | 10 | | 15 | 3 | | 16 | 3 | | 17 | 6 | | 18 | 14 | | 19 | 25 | | 20 | 9 | | 21 | 8 | | 22 | 7 | | 23 | 32 | | 24 | 2 | | 25 | 6 | | 26 | 4 | | 27 | 2 | | 28 | 4 | | 29 | 6 | | 30 | 9 | | 31 | 28 | | 32 | 4 | | 33 | 10 | | 34 | 26 | | 35 | 4 | | 36 | 2 | | 37 | 6 | | 38 | 4 | | 39 | 18 | | 40 | 8 | | 41 | 1 | | 42 | 1 | | 43 | 13 | | 44 | 22 | | 45 | 6 | | 46 | 15 | | 47 | 50 | | 48 | 7 | | 49 | 4 |
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| 63.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.42 | | totalSentences | 100 | | uniqueOpeners | 42 | |
| 58.48% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 57 | | matches | | 0 | "Then the recognition arrived all" |
| | ratio | 0.018 | |
| 93.68% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 57 | | matches | | 0 | "Her shift at the Golden" | | 1 | "She knew the voice before" | | 2 | "She was wearing a camel" | | 3 | "She smelled like rain and" | | 4 | "Her nails were the colour" | | 5 | "He poured the red." | | 6 | "His limp, Aurora noticed, was" | | 7 | "He caught Aurora's eye, gave" | | 8 | "It wasn't a question." | | 9 | "She had been eight when" | | 10 | "They had been friends like" | | 11 | "They had been friends in" | | 12 | "She drank instead." | | 13 | "She laughed, not kindly, at" | | 14 | "She was looking at her" | | 15 | "You kept the lot." | | 16 | "You carried it around in" | | 17 | "she heard herself say" |
| | ratio | 0.316 | |
| 21.40% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 57 | | matches | | 0 | "The green neon bled onto" | | 1 | "That was the story she" | | 2 | "Her shift at the Golden" | | 3 | "The Raven's Nest at half-nine" | | 4 | "The walls, as ever, wore" | | 5 | "Aurora slid onto a stool," | | 6 | "She knew the voice before" | | 7 | "The turn took a long" | | 8 | "Niamh Doherty stood in the" | | 9 | "Niamh laughed, short and disbelieving," | | 10 | "She was wearing a camel" | | 11 | "Niamh slid onto the next" | | 12 | "She smelled like rain and" | | 13 | "Her nails were the colour" | | 14 | "Niamh stared at her" | | 15 | "Silas came out from the" | | 16 | "He poured the red." | | 17 | "His limp, Aurora noticed, was" | | 18 | "He caught Aurora's eye, gave" | | 19 | "Niamh laughed again, more carefully" |
| | ratio | 0.877 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 96.77% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 2 | | matches | | 0 | "Niamh laughed again, more carefully this time, as if testing whether the old laugh still fit between them." | | 1 | "She had been eight when she got it, falling off the low wall behind her grandmother's house in Penarth, and Niamh had been nine, and had carried her home pressi…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 90.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 3 | | fancyTags | | 0 | "Niamh laughed (laugh)" | | 1 | "Aurora agreed (agree)" | | 2 | "she set (set)" |
| | dialogueSentences | 50 | | tagDensity | 0.26 | | leniency | 0.52 | | rawRatio | 0.231 | | effectiveRatio | 0.12 | |