| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.348 | | leniency | 0.696 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1389 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 64.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1389 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "warmth" | | 1 | "footsteps" | | 2 | "lurch" | | 3 | "pulse" | | 4 | "echo" | | 5 | "silence" | | 6 | "whisper" | | 7 | "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 | 105 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 105 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1409 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 1322 | | uniqueNames | 8 | | maxNameDensity | 0.23 | | worstName | "Eva" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Eva" | | discoveredNames | | Richmond | 2 | | Golden | 1 | | Empress | 1 | | London | 2 | | Eva | 3 | | Rory | 2 | | Evan | 1 | | December-cold | 1 |
| | persons | | | places | | 0 | "Richmond" | | 1 | "Golden" | | 2 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 77.54% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like a stampede" | | 1 | "appeared past the pond — seven of them in a ring on the far slope, and it took her a long moment to understand what she was seeing, because they weren't stone at all" |
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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 | 1409 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 118 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 29.35 | | std | 28.46 | | cv | 0.969 | | sampleLengths | | 0 | 17 | | 1 | 78 | | 2 | 49 | | 3 | 8 | | 4 | 8 | | 5 | 105 | | 6 | 14 | | 7 | 7 | | 8 | 39 | | 9 | 2 | | 10 | 11 | | 11 | 12 | | 12 | 20 | | 13 | 2 | | 14 | 5 | | 15 | 4 | | 16 | 4 | | 17 | 4 | | 18 | 58 | | 19 | 15 | | 20 | 7 | | 21 | 58 | | 22 | 37 | | 23 | 3 | | 24 | 1 | | 25 | 70 | | 26 | 34 | | 27 | 34 | | 28 | 78 | | 29 | 37 | | 30 | 51 | | 31 | 12 | | 32 | 21 | | 33 | 8 | | 34 | 88 | | 35 | 38 | | 36 | 47 | | 37 | 22 | | 38 | 63 | | 39 | 9 | | 40 | 94 | | 41 | 10 | | 42 | 71 | | 43 | 5 | | 44 | 6 | | 45 | 2 | | 46 | 39 | | 47 | 2 |
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| 98.58% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 105 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 200 | | matches | | 0 | "wasn't laughing" | | 1 | "was ignoring" | | 2 | "was seeing" | | 3 | "was following" | | 4 | "were still swaying" | | 5 | "wasn't just aching" | | 6 | "was tightening" | | 7 | "were moving" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 20 | | semicolonCount | 0 | | flaggedSentences | 16 | | totalSentences | 118 | | ratio | 0.136 | | matches | | 0 | "Aurora had felt it stirring since sunset — a faint warmth against her sternum that she kept mistaking for the start of a fever." | | 1 | "She could not remember his face — not that night, not since — only his voice." | | 2 | "She'd expected London to follow her in — the orange wash of streetlight over the walls, the grind of the roads, a plane dragging its silver noise across the sky." | | 3 | "Richmond's deer were a fact of her childhood — she'd come out here once with her mother, aged eight, and one had eaten half a sandwich out of her hand." | | 4 | "Thirty still shapes in the dark, watching with eyes that caught no light at all — flat and matte, like holes punched in the night." | | 5 | "And for a moment — she stopped, and listened — there was one footstep too many." | | 6 | "The stones appeared past the pond — seven of them in a ring on the far slope, and it took her a long moment to understand what she was seeing, because they weren't stone at all." | | 7 | "It beat against her sternum, and she realised with a lurch that it had found a rhythm — a slow pulse, like something sleeping." | | 8 | "They carpeted the whole clearing beyond the stones, hundreds of them, open and blooming in the dark the way flowers don't — petals spread wide at midnight as if it were noon." | | 9 | "Too many stars, in constellations she didn't know, and no orange glow anywhere — no London in any direction at all." | | 10 | "When she turned her back on them, she heard it — a whisper of fibres, a creak of small green necks turning in unison behind her." | | 11 | "She rubbed it with her thumb and felt the raised skin shifting under her fingers — and stopped, because it wasn't just aching." | | 12 | "Its faint inner glow, the one she'd half convinced herself she'd imagined, was gone — swallowed — and the pulse against her fingers had gone frantic, a small heart sprinting, faster than her own." | | 13 | "All at once, a whole swathe of them pressed flat, in a line, as if a body were moving through them — something wide, and slow, and patient — coming around the inside of the stone ring towards her." | | 14 | "\"Rory,\" said the flowers — no." | | 15 | "\"Malphora,\" said something right at her ear, in a voice like warm honey, like stems bending under weight, a name she had never heard in her life — spoken the way you speak to someone you've been waiting for." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1306 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.02450229709035222 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.002297090352220521 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 11.94 | | std | 9.58 | | cv | 0.802 | | sampleLengths | | 0 | 17 | | 1 | 24 | | 2 | 26 | | 3 | 28 | | 4 | 25 | | 5 | 8 | | 6 | 16 | | 7 | 8 | | 8 | 4 | | 9 | 4 | | 10 | 24 | | 11 | 7 | | 12 | 30 | | 13 | 9 | | 14 | 23 | | 15 | 12 | | 16 | 4 | | 17 | 10 | | 18 | 4 | | 19 | 3 | | 20 | 8 | | 21 | 4 | | 22 | 7 | | 23 | 20 | | 24 | 2 | | 25 | 9 | | 26 | 2 | | 27 | 10 | | 28 | 2 | | 29 | 14 | | 30 | 6 | | 31 | 2 | | 32 | 5 | | 33 | 4 | | 34 | 4 | | 35 | 4 | | 36 | 14 | | 37 | 1 | | 38 | 8 | | 39 | 9 | | 40 | 26 | | 41 | 5 | | 42 | 10 | | 43 | 7 | | 44 | 30 | | 45 | 8 | | 46 | 20 | | 47 | 2 | | 48 | 4 | | 49 | 3 |
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| 70.94% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.46153846153846156 | | totalSentences | 117 | | uniqueOpeners | 54 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 96 | | matches | | 0 | "Instead the dark closed behind" | | 1 | "Then it didn't land again." | | 2 | "Too many stars, in constellations" | | 3 | "Then it said 3:12." |
| | ratio | 0.042 | |
| 70.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 96 | | matches | | 0 | "She could remember his coat," | | 1 | "She could not remember his" | | 2 | "She'd laughed at him." | | 3 | "She wasn't laughing now." | | 4 | "She chained her bike to" | | 5 | "She'd expected London to follow" | | 6 | "Her breath hung in front" | | 7 | "She went left." | | 8 | "She rang Eva, because Eva" | | 9 | "She hung up before the" | | 10 | "She raised the phone and" | | 11 | "She put the phone away." | | 12 | "It felt heavier going in" | | 13 | "She knew what they were:" | | 14 | "She took the long way" | | 15 | "She hadn't heard them go." | | 16 | "It landed a half-beat after" | | 17 | "She had promised herself, after" | | 18 | "She was ignoring it now," | | 19 | "They were oaks." |
| | ratio | 0.375 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 96 | | matches | | 0 | "The pendant woke at half" | | 1 | "Aurora had felt it stirring" | | 2 | "The little crimson gem hung" | | 3 | "The stranger who'd given it" | | 4 | "She could remember his coat," | | 5 | "She could not remember his" | | 6 | "She'd laughed at him." | | 7 | "She wasn't laughing now." | | 8 | "She chained her bike to" | | 9 | "She'd expected London to follow" | | 10 | "The grass went on and" | | 11 | "Her breath hung in front" | | 12 | "The pendant pulled left." | | 13 | "She went left." | | 14 | "She rang Eva, because Eva" | | 15 | "Eva's voice arrived thick with" | | 16 | "Rory kept her stride even" | | 17 | "A rustle of duvet" | | 18 | "She hung up before the" | | 19 | "The clock hadn't moved since" |
| | ratio | 0.667 | |
| 52.08% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 96 | | matches | | 0 | "By the time she'd dropped" |
| | ratio | 0.01 | |
| 82.07% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 4 | | matches | | 0 | "The stranger who'd given it to her had been waiting outside the Golden Empress three nights ago, framed in the steamed-up doorway of the restaurant." | | 1 | "They carpeted the whole clearing beyond the stones, hundreds of them, open and blooming in the dark the way flowers don't — petals spread wide at midnight as if…" | | 2 | "The silence was total in a way that made her jaw ache, and her own voice sounded small and wet, like it had come from inside a sealed room." | | 3 | "All at once, a whole swathe of them pressed flat, in a line, as if a body were moving through them — something wide, and slow, and patient — coming around the i…" |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "she called, and the clearing swallowed the word" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 23 | | tagDensity | 0.217 | | leniency | 0.435 | | rawRatio | 0.2 | | effectiveRatio | 0.087 | |