| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.471 | | leniency | 0.941 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1321 | | 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) | |
| 73.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1321 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "flickered" | | 2 | "footsteps" | | 3 | "velvet" | | 4 | "stomach" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 89 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 89 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1321 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 1175 | | uniqueNames | 15 | | maxNameDensity | 0.34 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Greenland | 1 | | Road | 1 | | Quinn | 4 | | Camden | 3 | | Parkway | 1 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Town | 1 | | Three | 1 | | Vauxhall | 1 | | Morris | 2 | | Veil | 1 | | Market | 1 | | One | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Market" |
| | places | | 0 | "Greenland" | | 1 | "Road" | | 2 | "Camden" | | 3 | "Raven" | | 4 | "Soho" | | 5 | "Town" | | 6 | "Vauxhall" |
| | globalScore | 1 | | windowScore | 1 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 2 | | matches | | 0 | "something close to her ear" | | 1 | "sounded like a name" |
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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 | 1321 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 98 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 33.03 | | std | 26.11 | | cv | 0.791 | | sampleLengths | | 0 | 24 | | 1 | 68 | | 2 | 101 | | 3 | 21 | | 4 | 17 | | 5 | 14 | | 6 | 78 | | 7 | 6 | | 8 | 20 | | 9 | 70 | | 10 | 14 | | 11 | 57 | | 12 | 14 | | 13 | 11 | | 14 | 10 | | 15 | 30 | | 16 | 46 | | 17 | 13 | | 18 | 38 | | 19 | 24 | | 20 | 43 | | 21 | 54 | | 22 | 10 | | 23 | 7 | | 24 | 45 | | 25 | 20 | | 26 | 21 | | 27 | 116 | | 28 | 8 | | 29 | 57 | | 30 | 36 | | 31 | 56 | | 32 | 4 | | 33 | 21 | | 34 | 2 | | 35 | 45 | | 36 | 24 | | 37 | 34 | | 38 | 20 | | 39 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 175 | | matches | | 0 | "were breathing" | | 1 | "was buying" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 98 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1176 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.01870748299319728 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0017006802721088435 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 13.48 | | std | 10.76 | | cv | 0.798 | | sampleLengths | | 0 | 24 | | 1 | 11 | | 2 | 30 | | 3 | 21 | | 4 | 3 | | 5 | 3 | | 6 | 8 | | 7 | 33 | | 8 | 29 | | 9 | 22 | | 10 | 9 | | 11 | 21 | | 12 | 14 | | 13 | 3 | | 14 | 2 | | 15 | 12 | | 16 | 36 | | 17 | 6 | | 18 | 5 | | 19 | 31 | | 20 | 6 | | 21 | 2 | | 22 | 18 | | 23 | 4 | | 24 | 22 | | 25 | 22 | | 26 | 6 | | 27 | 16 | | 28 | 4 | | 29 | 3 | | 30 | 7 | | 31 | 27 | | 32 | 14 | | 33 | 16 | | 34 | 12 | | 35 | 2 | | 36 | 7 | | 37 | 4 | | 38 | 10 | | 39 | 6 | | 40 | 1 | | 41 | 17 | | 42 | 2 | | 43 | 2 | | 44 | 2 | | 45 | 9 | | 46 | 37 | | 47 | 13 | | 48 | 12 | | 49 | 26 |
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| 59.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.42857142857142855 | | totalSentences | 98 | | uniqueOpeners | 42 | |
| 43.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 76 | | matches | | 0 | "Then he'd stopped at the" |
| | ratio | 0.013 | |
| 51.58% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 76 | | matches | | 0 | "She blinked it away and" | | 1 | "He'd made her at the" | | 2 | "She'd tailed him from the" | | 3 | "He'd dropped his coffee in" | | 4 | "he shouted over his shoulder," | | 5 | "She filed the phrase away" | | 6 | "He cut left through the" | | 7 | "She lungled for the bag's" | | 8 | "Her fingers closed on nylon." | | 9 | "He twisted, sharp and practised," | | 10 | "She looked down at her" | | 11 | "She gave it three seconds," | | 12 | "Her radio spat static." | | 13 | "She'd expected that." | | 14 | "He stared at the token" | | 15 | "She held it up" | | 16 | "She kept her face flat" | | 17 | "He laughed then, and there" | | 18 | "He straightened up and rapped" | | 19 | "He tapped the bag at" |
| | ratio | 0.421 | |
| 45.53% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 76 | | matches | | 0 | "The runner vaulted the hoarding" | | 1 | "Rain drove sideways off the" | | 2 | "She blinked it away and" | | 3 | "Glass on glass." | | 4 | "Something in bottles." | | 5 | "He'd made her at the" | | 6 | "She'd tailed him from the" | | 7 | "He'd dropped his coffee in" | | 8 | "he shouted over his shoulder," | | 9 | "She filed the phrase away" | | 10 | "He cut left through the" | | 11 | "She lungled for the bag's" | | 12 | "Her fingers closed on nylon." | | 13 | "He twisted, sharp and practised," | | 14 | "She looked down at her" | | 15 | "The building swallowed him." | | 16 | "She gave it three seconds," | | 17 | "The steps descended past signage" | | 18 | "Camden Town it had said" | | 19 | "Her radio spat static." |
| | ratio | 0.829 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 76 | | matches | | 0 | "Now they were deep in" | | 1 | "Now it said CAMDEN TW" |
| | ratio | 0.026 | |
| 6.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 8 | | matches | | 0 | "Ahead, the runner's courier bag bounced against his spine, its contents clinking in a rhythm she could track without seeing him." | | 1 | "Beyond it, a warm amber glow that flickered like candlelight and moved like water." | | 2 | "The lock turned over with a sound like a bone snapping, and the gate swung inward a metre, just a metre, exhaling warm air that smelled of myrrh and hot copper …" | | 3 | "Stalls crowded the platform edge and spilled across the dead tracks, lit by strings of glass bulbs that dimmed and brightened in slow unison, as if the light it…" | | 4 | "She saw jars of things that turned to watch her pass." | | 5 | "The crowd moved between the stalls in a low murmur, and half of them were wrong in small ways she couldn't name at first, then could: too many joints in the fin…" | | 6 | "Quinn drifted closer, past a stall selling maps of places that shifted under your fingers, past a child no taller than her knee who was buying teeth by the hand…" | | 7 | "A hundred faces turned toward her at once, some of them wearing expressions, some of them wearing things that had learned expressions." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 17 | | tagDensity | 0.235 | | leniency | 0.471 | | rawRatio | 0.25 | | effectiveRatio | 0.118 | |