| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1110 | | 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) | |
| 72.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1110 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "warmth" | | 1 | "pulse" | | 2 | "echo" | | 3 | "weight" | | 4 | "resolve" |
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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 | 94 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 94 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 99 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1120 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 1107 | | uniqueNames | 9 | | maxNameDensity | 0.9 | | worstName | "Fact" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Fact" | | discoveredNames | | Eva | 2 | | Golden | 1 | | Empress | 1 | | Heathrow | 1 | | London | 2 | | Cardiff | 2 | | Pontcanna | 1 | | Rory | 4 | | Fact | 10 |
| | persons | | | places | | 0 | "London" | | 1 | "Cardiff" | | 2 | "Pontcanna" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 70.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like rudeness toward a stranger wh" | | 1 | "sounded like that" |
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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 | 1120 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 99 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 33.94 | | std | 26.67 | | cv | 0.786 | | sampleLengths | | 0 | 32 | | 1 | 97 | | 2 | 70 | | 3 | 65 | | 4 | 53 | | 5 | 21 | | 6 | 68 | | 7 | 47 | | 8 | 20 | | 9 | 43 | | 10 | 57 | | 11 | 6 | | 12 | 27 | | 13 | 2 | | 14 | 43 | | 15 | 31 | | 16 | 22 | | 17 | 58 | | 18 | 48 | | 19 | 93 | | 20 | 1 | | 21 | 43 | | 22 | 1 | | 23 | 26 | | 24 | 10 | | 25 | 4 | | 26 | 14 | | 27 | 39 | | 28 | 1 | | 29 | 7 | | 30 | 59 | | 31 | 7 | | 32 | 5 |
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| 94.06% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 94 | | matches | | 0 | "get struck" | | 1 | "was bracken " | | 2 | "being called" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 166 | | matches | | 0 | "was trespassing" | | 1 | "was learning" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 2 | | flaggedSentences | 11 | | totalSentences | 99 | | ratio | 0.111 | | matches | | 0 | "Not with light — with heat." | | 1 | "She'd delivered for the Golden Empress through every borough at every hour, and the city always made noise — the drone of the A-roads, the Heathrow stack stacking up overhead, the mains hum beneath it all." | | 2 | "Fact: a fox screamed off to her left like a murdered woman, and that meant nothing; foxes always sounded like that." | | 3 | "A buck that size doesn't vanish from frost-crisp ground without a sound — yet the whole park felt emptied of its deer at once, like a room cleared for a fight." | | 4 | "One stride, bracken at her hips; the next, short grass silvered with frost, and the ring." | | 5 | "Not stones — oaks." | | 6 | "She turned to fix her line out — the gap between two dead oaks, the bracken beyond, the way she'd come — and saw her own footprints crossing the frost behind her, dark commas on silver." | | 7 | "Three notes, then three again, then the same three with something folded inside them — a syllable." | | 8 | "She turned her head slow, because fast made things happen, and it was bracken — white-fronded, moonlit, nothing." | | 9 | "Eva's voice from the right — bright, hoarse, the voice that had said get on the train, just get on the train." | | 10 | "Heat bloomed against her sternum like a coal taking breath, and red light threw itself across the frost, up under her chin, out over the clearing — and a shadow lay on the grass at her feet that was not hers." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1100 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.02181818181818182 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0009090909090909091 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 99 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 99 | | mean | 11.31 | | std | 10.29 | | cv | 0.91 | | sampleLengths | | 0 | 6 | | 1 | 24 | | 2 | 2 | | 3 | 8 | | 4 | 6 | | 5 | 40 | | 6 | 12 | | 7 | 31 | | 8 | 4 | | 9 | 36 | | 10 | 2 | | 11 | 28 | | 12 | 3 | | 13 | 3 | | 14 | 6 | | 15 | 8 | | 16 | 21 | | 17 | 24 | | 18 | 9 | | 19 | 8 | | 20 | 5 | | 21 | 31 | | 22 | 5 | | 23 | 16 | | 24 | 4 | | 25 | 34 | | 26 | 9 | | 27 | 16 | | 28 | 5 | | 29 | 9 | | 30 | 1 | | 31 | 1 | | 32 | 1 | | 33 | 13 | | 34 | 22 | | 35 | 16 | | 36 | 4 | | 37 | 9 | | 38 | 8 | | 39 | 26 | | 40 | 13 | | 41 | 3 | | 42 | 5 | | 43 | 36 | | 44 | 6 | | 45 | 1 | | 46 | 8 | | 47 | 18 | | 48 | 2 | | 49 | 7 |
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| 82.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.5463917525773195 | | totalSentences | 97 | | uniqueOpeners | 53 | |
| 40.65% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 82 | | matches | | | ratio | 0.012 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 82 | | matches | | 0 | "It had arrived in the" | | 1 | "She'd delivered for the Golden" | | 2 | "She listed facts." | | 3 | "She never heard it go." | | 4 | "She pitched her voice at" | | 5 | "She crossed to the nearest" | | 6 | "She turned to fix her" | | 7 | "They paralleled hers for six" | | 8 | "She pressed her tongue to" | | 9 | "She didn't look up." | | 10 | "They faced her now." | | 11 | "She thumbed her phone awake." | | 12 | "She counted out sixty breaths" | | 13 | "She turned her head slow," | | 14 | "She looked back at the" | | 15 | "It only waited, at the" | | 16 | "Her mother's voice, out of" | | 17 | "Her mother was asleep in" |
| | ratio | 0.22 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 51 | | totalSentences | 82 | | matches | | 0 | "The fence wire bit her" | | 1 | "Rory dropped into the park" | | 2 | "It had arrived in the" | | 3 | "Tonight the heat had gone" | | 4 | "That was the part she" | | 5 | "London never shut up." | | 6 | "She'd delivered for the Golden" | | 7 | "She listed facts." | | 8 | "Facts held still." | | 9 | "A fallow buck watched her" | | 10 | "She never heard it go." | | 11 | "A buck that size doesn't" | | 12 | "The trees opened without warning." | | 13 | "Campions, foxgloves, white violets open" | | 14 | "November had no business here." | | 15 | "A pulse, patient as a" | | 16 | "She pitched her voice at" | | 17 | "The clearing took the words" | | 18 | "The frost swallowed her voice" | | 19 | "She crossed to the nearest" |
| | ratio | 0.622 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 67.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 4 | | matches | | 0 | "Rory dropped into the park on the wrong side of midnight and stood in the hawthorn's shadow, breathing fog, listening for the city's answer." | | 1 | "No orange glow above the tree line either, as though someone had drawn a curtain around the park and London stood on the other side of it, unaware." | | 2 | "Heat bloomed against her sternum like a coal taking breath, and red light threw itself across the frost, up under her chin, out over the clearing — and a shadow…" | | 3 | "Cast forward, toward her, which meant something stood between her and the light." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |