| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "Rory leaned back [back]" |
| | dialogueSentences | 55 | | tagDensity | 0.291 | | leniency | 0.582 | | rawRatio | 0.063 | | effectiveRatio | 0.036 | |
| 89.47% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1424 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "very" | | 1 | "lightly" | | 2 | "really" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 89.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1424 | | totalAiIsms | 3 | | 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 | 1 | | narrationSentences | 63 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 63 | | 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 | 80 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1437 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 892 | | uniqueNames | 11 | | maxNameDensity | 1.91 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 17 | | Soho | 1 | | Wardour | 1 | | Street | 1 | | Nest | 1 | | Tuesday | 1 | | Czech | 1 | | Prague | 2 | | June | 1 | | Eva | 14 | | Silas | 3 |
| | persons | | | places | | 0 | "Soho" | | 1 | "Wardour" | | 2 | "Street" | | 3 | "Nest" | | 4 | "Prague" |
| | globalScore | 0.547 | | windowScore | 0.5 | |
| 95.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 1 | | matches | | 0 | "something close to a laugh" |
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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 | 1437 | | 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 | 55 | | mean | 26.13 | | std | 21.84 | | cv | 0.836 | | sampleLengths | | 0 | 65 | | 1 | 45 | | 2 | 3 | | 3 | 20 | | 4 | 79 | | 5 | 16 | | 6 | 59 | | 7 | 30 | | 8 | 1 | | 9 | 19 | | 10 | 1 | | 11 | 50 | | 12 | 18 | | 13 | 3 | | 14 | 13 | | 15 | 27 | | 16 | 12 | | 17 | 35 | | 18 | 50 | | 19 | 43 | | 20 | 11 | | 21 | 16 | | 22 | 10 | | 23 | 54 | | 24 | 31 | | 25 | 8 | | 26 | 31 | | 27 | 17 | | 28 | 13 | | 29 | 2 | | 30 | 2 | | 31 | 17 | | 32 | 48 | | 33 | 20 | | 34 | 4 | | 35 | 9 | | 36 | 38 | | 37 | 4 | | 38 | 25 | | 39 | 7 | | 40 | 47 | | 41 | 21 | | 42 | 16 | | 43 | 4 | | 44 | 95 | | 45 | 40 | | 46 | 30 | | 47 | 48 | | 48 | 6 | | 49 | 6 |
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| 94.12% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 63 | | matches | | 0 | "being asked" | | 1 | "was buttoned" |
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| 13.52% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 143 | | matches | | 0 | "was still hammering" | | 1 | "were standing" | | 2 | "were shaking" | | 3 | "was folding" |
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| 56.28% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 99 | | ratio | 0.03 | | matches | | 0 | "One of the maps on the wall — the Czech one, framed above the booth by the fire — caught her eye the way it did most nights, the little red pin over Prague she'd never asked about." | | 1 | "The second wrong thing was her hair — mousy, flat, pinned back — because Rory had last seen that hair the color of a struck match, teased out like a bonfire the woman had been proud of." | | 2 | "She snatched it up — snatched, that was the word for it, a movement with fear in its knuckles — read the screen, and typed something fast with her thumbs, a message with the cadence of a schoolgirl finishing homework before inspection." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 759 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.025032938076416336 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003952569169960474 | |
| 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 | 14.52 | | std | 13.53 | | cv | 0.932 | | sampleLengths | | 0 | 35 | | 1 | 20 | | 2 | 10 | | 3 | 13 | | 4 | 32 | | 5 | 3 | | 6 | 9 | | 7 | 11 | | 8 | 10 | | 9 | 26 | | 10 | 5 | | 11 | 38 | | 12 | 16 | | 13 | 22 | | 14 | 37 | | 15 | 6 | | 16 | 5 | | 17 | 19 | | 18 | 1 | | 19 | 7 | | 20 | 12 | | 21 | 1 | | 22 | 3 | | 23 | 47 | | 24 | 12 | | 25 | 6 | | 26 | 3 | | 27 | 13 | | 28 | 11 | | 29 | 16 | | 30 | 12 | | 31 | 29 | | 32 | 6 | | 33 | 8 | | 34 | 42 | | 35 | 11 | | 36 | 32 | | 37 | 11 | | 38 | 16 | | 39 | 10 | | 40 | 36 | | 41 | 7 | | 42 | 4 | | 43 | 7 | | 44 | 31 | | 45 | 5 | | 46 | 3 | | 47 | 7 | | 48 | 24 | | 49 | 11 |
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| 47.47% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.36363636363636365 | | totalSentences | 99 | | uniqueOpeners | 36 | |
| 55.56% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 60 | | matches | | 0 | "Then she stopped turning it." |
| | ratio | 0.017 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 60 | | matches | | 0 | "Her last delivery had gone" | | 1 | "She counted neither as she" | | 2 | "She hoisted herself onto her" | | 3 | "He set down a lager" | | 4 | "She stared at Rory across" | | 5 | "They didn't hug." | | 6 | "He didn't offer a hand," | | 7 | "They took the booth beneath" | | 8 | "She said it lightly, but" | | 9 | "She turned the wine glass" | | 10 | "Her wedding ring caught the" | | 11 | "She kept spinning it." | | 12 | "She snatched it up —" | | 13 | "she offered, putting the phone" | | 14 | "Her hand went to her" | | 15 | "She looked at Eva's face" | | 16 | "He'd stopped polishing." | | 17 | "Her fingers found the ring" | | 18 | "She picked the phone up," | | 19 | "She drew the cardigan's top" |
| | ratio | 0.333 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 60 | | matches | | 0 | "The rain had chased Rory" | | 1 | "Her last delivery had gone" | | 2 | "She counted neither as she" | | 3 | "The green neon bled through" | | 4 | "Silas stood behind the bar" | | 5 | "She hoisted herself onto her" | | 6 | "He set down a lager" | | 7 | "The Tuesday crowd was three" | | 8 | "Rain ticked against the window." | | 9 | "The door opened, letting in" | | 10 | "The woman who came in" | | 11 | "The second wrong thing was" | | 12 | "The woman stopped in the" | | 13 | "Water dripped off her shoulder." | | 14 | "She stared at Rory across" | | 15 | "Rory's hand went still around" | | 16 | "They didn't hug." | | 17 | "Eva came forward in small" | | 18 | "Eva's gaze moved over her," | | 19 | "Rory managed something close to" |
| | ratio | 0.933 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "Eva came forward in small steps, as though the floor might not hold her, and then they were standing in front of each other, and Eva's hands were shaking, and R…" | | 1 | "She drew the cardigan's top button through its hole, and then the second one, and folded her bare hands around the warm glass as if they'd been cold a long time…" |
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| 93.75% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 1 | | matches | | 0 | "She said, but her eyes went somewhere else when she said it" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Rory repeated (repeat)" |
| | dialogueSentences | 55 | | tagDensity | 0.055 | | leniency | 0.109 | | rawRatio | 0.333 | | effectiveRatio | 0.036 | |