| 13.95% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 4 | | adverbTags | | 0 | "Megan pulled back [back]" | | 1 | "She glanced around [around]" | | 2 | "Megan said quietly [quietly]" | | 3 | "she said finally [finally]" |
| | dialogueSentences | 43 | | tagDensity | 0.419 | | leniency | 0.837 | | rawRatio | 0.222 | | effectiveRatio | 0.186 | |
| 82.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1165 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slowly" | | 1 | "slightly" | | 2 | "very" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 78.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1165 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "scanning" | | 1 | "efficient" | | 2 | "familiar" | | 3 | "comfortable" |
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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 | 74 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 74 | | filterMatches | | | hedgeMatches | | |
| 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 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1174 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 935 | | uniqueNames | 17 | | maxNameDensity | 2.14 | | worstName | "Megan" | | maxWindowNameDensity | 4 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Tuesdays | 1 | | Guinness | 2 | | Davies | 1 | | Rory | 17 | | Megan | 20 | | City | 1 | | Road | 1 | | Silas | 3 | | Sauvignon | 1 | | Blanc | 1 | | Clifford | 1 | | Chance | 1 | | Canary | 1 | | Wharf | 1 | | Bridgend | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Guinness" | | 3 | "Davies" | | 4 | "Rory" | | 5 | "Megan" | | 6 | "Silas" | | 7 | "Clifford" | | 8 | "Chance" |
| | places | | | globalScore | 0.43 | | windowScore | 0.333 | |
| 47.96% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a different person wearing a" | | 1 | "looked like when it had four years to mat" |
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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 | 1174 | | 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 | 51 | | mean | 23.02 | | std | 24.06 | | cv | 1.045 | | sampleLengths | | 0 | 104 | | 1 | 33 | | 2 | 18 | | 3 | 27 | | 4 | 45 | | 5 | 90 | | 6 | 3 | | 7 | 8 | | 8 | 6 | | 9 | 72 | | 10 | 33 | | 11 | 15 | | 12 | 35 | | 13 | 4 | | 14 | 38 | | 15 | 3 | | 16 | 13 | | 17 | 12 | | 18 | 30 | | 19 | 1 | | 20 | 4 | | 21 | 9 | | 22 | 22 | | 23 | 21 | | 24 | 88 | | 25 | 22 | | 26 | 5 | | 27 | 14 | | 28 | 3 | | 29 | 5 | | 30 | 32 | | 31 | 3 | | 32 | 15 | | 33 | 16 | | 34 | 41 | | 35 | 31 | | 36 | 3 | | 37 | 8 | | 38 | 74 | | 39 | 13 | | 40 | 3 | | 41 | 27 | | 42 | 3 | | 43 | 10 | | 44 | 42 | | 45 | 10 | | 46 | 17 | | 47 | 7 | | 48 | 19 | | 49 | 6 |
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| 95.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 74 | | matches | | 0 | "being asked" | | 1 | "got remarried " |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 165 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 99 | | ratio | 0.071 | | matches | | 0 | "By nine, only a few regulars occupied the far end of the bar — a retired postman who nursed a Guinness like it was a project, and a woman in her fifties who always ordered gin and tonic and never spoke to anyone." | | 1 | "A laugh — a sharp, bright laugh, cut off almost immediately, as though the person thought better of it." | | 2 | "She smelled different too — cedar and something dry and expensive, not the patchouli oil she used to buy from the market on City Road." | | 3 | "Her expression didn't shift dramatically — Rory had to give her that — but something in her jaw softened, and that was almost worse." | | 4 | "She lived in Canary Wharf in a flat that she described as \"aggressively sensible.\" Her mother had got remarried — someone from Bridgend, retired teacher, Megan thought her mother deserved it." | | 5 | "Someone somewhere put music on low — something Rory didn't recognise, a guitar and a voice at a distance." | | 6 | "She looked at Megan — at the coat and the hair and the careful, competent face — and understood that this was what guilt looked like when it had four years to mature." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 926 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.03995680345572354 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.012958963282937365 | |
| 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 | 11.86 | | std | 9.83 | | cv | 0.829 | | sampleLengths | | 0 | 7 | | 1 | 43 | | 2 | 23 | | 3 | 31 | | 4 | 13 | | 5 | 20 | | 6 | 18 | | 7 | 12 | | 8 | 15 | | 9 | 8 | | 10 | 19 | | 11 | 18 | | 12 | 35 | | 13 | 17 | | 14 | 28 | | 15 | 10 | | 16 | 3 | | 17 | 7 | | 18 | 1 | | 19 | 5 | | 20 | 1 | | 21 | 7 | | 22 | 35 | | 23 | 5 | | 24 | 25 | | 25 | 18 | | 26 | 15 | | 27 | 14 | | 28 | 1 | | 29 | 25 | | 30 | 10 | | 31 | 4 | | 32 | 2 | | 33 | 22 | | 34 | 14 | | 35 | 3 | | 36 | 10 | | 37 | 3 | | 38 | 6 | | 39 | 6 | | 40 | 3 | | 41 | 24 | | 42 | 3 | | 43 | 1 | | 44 | 4 | | 45 | 9 | | 46 | 11 | | 47 | 11 | | 48 | 21 | | 49 | 11 |
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| 54.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.37373737373737376 | | totalSentences | 99 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 66 | | matches | | 0 | "Then Megan crossed the room" | | 1 | "Then Megan turned her wine" |
| | ratio | 0.03 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 66 | | matches | | 0 | "He'd taken one look at" | | 1 | "She wrapped both hands around" | | 2 | "He moved off to wipe" | | 3 | "She didn't look up until" | | 4 | "She wore a charcoal coat" | | 5 | "Her hair, which Rory remembered" | | 6 | "She looked like a different" | | 7 | "Their eyes met." | | 8 | "She smelled different too —" | | 9 | "Her eyes were moving over" | | 10 | "She glanced around at the" | | 11 | "Her expression didn't shift dramatically" | | 12 | "It was the same laugh" | | 13 | "They talked around it for" | | 14 | "She lived in Canary Wharf" | | 15 | "It wasn't a question." | | 16 | "She'd been the last to" | | 17 | "She looked at Megan —" | | 18 | "she said finally" |
| | ratio | 0.288 | |
| 5.45% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 66 | | matches | | 0 | "The Raven's Nest emptied early" | | 1 | "The old maps on the" | | 2 | "Rory sat on a stool" | | 3 | "Silas set a glass of" | | 4 | "He'd taken one look at" | | 5 | "She wrapped both hands around" | | 6 | "He moved off to wipe" | | 7 | "The door opened behind her" | | 8 | "She didn't look up until" | | 9 | "A laugh — a sharp," | | 10 | "A laugh she hadn't heard" | | 11 | "Megan Davies stood just inside" | | 12 | "She wore a charcoal coat" | | 13 | "Her hair, which Rory remembered" | | 14 | "She looked like a different" | | 15 | "Their eyes met." | | 16 | "Megan's hand dropped from the" | | 17 | "Rory set down her wine." | | 18 | "Rory's arms went around her." | | 19 | "She smelled different too —" |
| | ratio | 0.909 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 6 | | matches | | 0 | "A laugh — a sharp, bright laugh, cut off almost immediately, as though the person thought better of it." | | 1 | "Megan Davies stood just inside the doorway, her hand still on the door handle, scanning the room with the efficient squint of someone who'd walked into the wron…" | | 2 | "She wore a charcoal coat that fitted her like it had been cut for her body specifically." | | 3 | "Then Megan crossed the room in quick steps and pulled her off the stool into a hug that was fiercer than Rory expected, the kind of hug that said something word…" | | 4 | "Megan ordered a Sauvignon Blanc with the easy authority of someone who made requests all day, and they settled onto the stools." | | 5 | "Silas brought her wine and disappeared again with the practised discretion of a man who understood when a room needed space." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 2 | | matches | | 0 | "Megan pulled back, both hands still gripping Rory's arms" | | 1 | "She glanced around, the photographs, the postman with his Guinness" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 2 | | fancyTags | | 0 | "She lived (live)" | | 1 | "Megan turned (turn)" |
| | dialogueSentences | 43 | | tagDensity | 0.186 | | leniency | 0.372 | | rawRatio | 0.25 | | effectiveRatio | 0.093 | |