| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.213 | | leniency | 0.426 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1707 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 79.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1707 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "loomed" | | 1 | "dancing" | | 2 | "trembled" | | 3 | "weight" | | 4 | "etched" | | 5 | "magnetic" | | 6 | "chill" |
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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 | 143 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 143 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 180 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 14 | | totalWords | 1707 | | ratio | 0.008 | | matches | | 0 | "Light from the side, Harlow. Shadows tell you what the eye skips." | | 1 | "E. Kowalski." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 1302 | | uniqueNames | 22 | | maxNameDensity | 1.08 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rawlings" | | discoveredNames | | Camden | 1 | | Rawlings | 13 | | Bovril | 1 | | Quinn | 14 | | Hackney | 1 | | Crown | 1 | | Prosecution | 1 | | Service | 1 | | Morris | 2 | | Harlow | 1 | | Christmas | 1 | | Okafor | 7 | | Daniel | 2 | | Reyes | 2 | | Kentish | 1 | | Town | 1 | | Oyster | 1 | | British | 1 | | Museum | 1 | | Thames | 1 | | Wapping | 1 | | Further | 1 |
| | persons | | 0 | "Rawlings" | | 1 | "Bovril" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Okafor" | | 5 | "Daniel" | | 6 | "Reyes" |
| | places | | 0 | "Hackney" | | 1 | "Christmas" | | 2 | "Kentish" | | 3 | "Town" | | 4 | "Thames" | | 5 | "Wapping" |
| | globalScore | 0.962 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like no alphabet she'd ever seen o" |
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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 | 1707 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 180 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 80 | | mean | 21.34 | | std | 22.54 | | cv | 1.056 | | sampleLengths | | 0 | 19 | | 1 | 60 | | 2 | 28 | | 3 | 7 | | 4 | 11 | | 5 | 5 | | 6 | 107 | | 7 | 3 | | 8 | 55 | | 9 | 3 | | 10 | 17 | | 11 | 15 | | 12 | 2 | | 13 | 46 | | 14 | 24 | | 15 | 3 | | 16 | 6 | | 17 | 3 | | 18 | 22 | | 19 | 8 | | 20 | 54 | | 21 | 4 | | 22 | 14 | | 23 | 5 | | 24 | 6 | | 25 | 58 | | 26 | 2 | | 27 | 39 | | 28 | 12 | | 29 | 5 | | 30 | 3 | | 31 | 64 | | 32 | 6 | | 33 | 6 | | 34 | 51 | | 35 | 3 | | 36 | 45 | | 37 | 1 | | 38 | 85 | | 39 | 6 | | 40 | 1 | | 41 | 4 | | 42 | 73 | | 43 | 32 | | 44 | 7 | | 45 | 14 | | 46 | 11 | | 47 | 3 | | 48 | 14 | | 49 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 143 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 180 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 180 | | ratio | 0.006 | | matches | | 0 | "The tunnel ran north-south; she'd checked the map in the car." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1307 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.026013771996939557 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0038255547054322878 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 180 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 180 | | mean | 9.48 | | std | 8.55 | | cv | 0.902 | | sampleLengths | | 0 | 19 | | 1 | 17 | | 2 | 2 | | 3 | 10 | | 4 | 10 | | 5 | 21 | | 6 | 19 | | 7 | 9 | | 8 | 7 | | 9 | 11 | | 10 | 5 | | 11 | 13 | | 12 | 15 | | 13 | 11 | | 14 | 13 | | 15 | 25 | | 16 | 8 | | 17 | 6 | | 18 | 1 | | 19 | 1 | | 20 | 14 | | 21 | 3 | | 22 | 45 | | 23 | 10 | | 24 | 3 | | 25 | 17 | | 26 | 7 | | 27 | 8 | | 28 | 2 | | 29 | 18 | | 30 | 28 | | 31 | 24 | | 32 | 3 | | 33 | 6 | | 34 | 3 | | 35 | 5 | | 36 | 6 | | 37 | 11 | | 38 | 8 | | 39 | 54 | | 40 | 4 | | 41 | 14 | | 42 | 5 | | 43 | 4 | | 44 | 2 | | 45 | 8 | | 46 | 15 | | 47 | 23 | | 48 | 4 | | 49 | 2 |
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| 80.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.5166666666666667 | | totalSentences | 180 | | uniqueOpeners | 93 | |
| 86.96% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 115 | | matches | | 0 | "Somewhere down the tunnel, water" | | 1 | "Soft brown leather, swollen with" | | 2 | "Further away than six yards." |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 115 | | matches | | 0 | "His hair lay plastered to" | | 1 | "He pocketed the vape anyway." | | 2 | "She had the tired, patient" | | 3 | "She didn't look happy about" | | 4 | "Her own brogues." | | 5 | "He lay in the middle" | | 6 | "He scratched the back of" | | 7 | "He liked a story that" | | 8 | "She angled the torch low," | | 9 | "She walked to the nearest" | | 10 | "She leaned in and caught" | | 11 | "It rolled into her palm" | | 12 | "She knew which way north" | | 13 | "She took three steps to" | | 14 | "She walked towards the wall." | | 15 | "Her glove hovered an inch" | | 16 | "Her left wrist itched under" | | 17 | "She checked it by reflex." | | 18 | "He stood over the body" | | 19 | "Her face went slack." |
| | ratio | 0.183 | |
| 90.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 115 | | matches | | 0 | "The dead man had drowned" | | 1 | "Quinn crouched beside him on" | | 2 | "His hair lay plastered to" | | 3 | "A thin trickle of water" | | 4 | "DS Rawlings loomed over her" | | 5 | "He pocketed the vape anyway." | | 6 | "Quinn stood and let her" | | 7 | "The station had died sometime" | | 8 | "Oxblood tiles climbed the curved" | | 9 | "A poster for Bovril peeled" | | 10 | "Someone had painted over the" | | 11 | "The air tasted of iron" | | 12 | "The only water for a" | | 13 | "Rawlings jerked his thumb at" | | 14 | "Quinn looked back at the" | | 15 | "The pathologist knelt on the" | | 16 | "She had the tired, patient" | | 17 | "She didn't look happy about" | | 18 | "Rawlings clapped his hands together," | | 19 | "Rawlings opened his mouth." |
| | ratio | 0.739 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 115 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 2 | | matches | | 0 | "The needle stiffened as she went, trembling less, pointing harder, like a dog on a lead that smells something in the hedge." | | 1 | "A small square of wet tiles, no wider than a doorframe, in a wall that should have been bone dry." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 47 | | tagDensity | 0.128 | | leniency | 0.255 | | rawRatio | 0.167 | | effectiveRatio | 0.043 | |