| 70.97% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said evenly [evenly]" | | 1 | "she said quietly [quietly]" |
| | dialogueSentences | 31 | | tagDensity | 0.452 | | leniency | 0.903 | | rawRatio | 0.143 | | effectiveRatio | 0.129 | |
| 89.42% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1418 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 82.37% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1418 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "weight" | | 1 | "stomach" | | 2 | "familiar" | | 3 | "etched" | | 4 | "standard" |
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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 | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 77 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 94 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1429 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 1108 | | uniqueNames | 9 | | maxNameDensity | 0.81 | | worstName | "Reyes" | | maxWindowNameDensity | 2 | | worstWindowName | "Reyes" | | discoveredNames | | Quinn | 6 | | Tube | 1 | | Borough | 1 | | Council | 1 | | Marcus | 1 | | Reyes | 9 | | Maglite | 1 | | Morris | 2 | | Oxford | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Marcus" | | 2 | "Reyes" | | 3 | "Morris" |
| | places | | 0 | "Borough" | | 1 | "Council" | | 2 | "Oxford" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.7 | | wordCount | 1429 | | matches | | 0 | "not the layers of a rough sleeper, but the deliberate dress of someone who'd chosen to come somewhe" |
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| 95.74% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 94 | | matches | | 0 | "marking that she arrived, that the" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 34.85 | | std | 29.61 | | cv | 0.85 | | sampleLengths | | 0 | 78 | | 1 | 12 | | 2 | 65 | | 3 | 3 | | 4 | 23 | | 5 | 81 | | 6 | 9 | | 7 | 92 | | 8 | 51 | | 9 | 16 | | 10 | 82 | | 11 | 9 | | 12 | 75 | | 13 | 3 | | 14 | 5 | | 15 | 47 | | 16 | 12 | | 17 | 104 | | 18 | 4 | | 19 | 20 | | 20 | 7 | | 21 | 88 | | 22 | 55 | | 23 | 10 | | 24 | 25 | | 25 | 2 | | 26 | 14 | | 27 | 78 | | 28 | 21 | | 29 | 43 | | 30 | 33 | | 31 | 19 | | 32 | 13 | | 33 | 45 | | 34 | 26 | | 35 | 15 | | 36 | 46 | | 37 | 26 | | 38 | 4 | | 39 | 56 | | 40 | 12 |
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| 87.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 77 | | matches | | 0 | "been sealed" | | 1 | "been pulled" | | 2 | "been swept" | | 3 | "been lifted" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 183 | | matches | | 0 | "was already saying" | | 1 | "wasn't lying" | | 2 | "was not pointing" | | 3 | "was pointing" | | 4 | "was pulling" | | 5 | "was already saying" | | 6 | "was, looking" | | 7 | "wasn't looking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 94 | | ratio | 0.085 | | matches | | 0 | "The old Tube station had been sealed since the seventies — she'd checked the records on the drive over, because checking records was the kind of thing that kept her hands from shaking." | | 1 | "Quinn adjusted the worn leather strap of the watch on her wrist — an old habit, a way of marking that she had arrived, that the clock had started — and walked the length of the platform with the unhurried, deliberate stride that eighteen years had taught her." | | 2 | "Not perfectly — there were drifts in the corners, against the cracked tile skirting — but the central walkway was clean." | | 3 | "He wore a long oilcloth coat, good boots, a knitted scarf — not the layers of a rough sleeper, but the deliberate dress of someone who'd chosen to come somewhere cold and wanted to be ready for it." | | 4 | "\"Maybe.\" She crouched at the trench's edge, careful not to disturb the gravel, and studied the dark crust on the concrete lip — the impact point." | | 5 | "And there — pressed into the silt beside the body, half-filled by seepage but unmistakable — the prints." | | 6 | "That was the thing about Reyes — she'd worked beside him for years, and he didn't have the talent for it." | | 7 | "A small brass compass lay against his palm, its casing green with verdigris, its face etched with markings she didn't recognise — angular, deliberate, almost like writing." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1104 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.030797101449275364 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.010869565217391304 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 94 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 94 | | mean | 15.2 | | std | 11.9 | | cv | 0.783 | | sampleLengths | | 0 | 22 | | 1 | 33 | | 2 | 10 | | 3 | 13 | | 4 | 12 | | 5 | 18 | | 6 | 27 | | 7 | 20 | | 8 | 3 | | 9 | 15 | | 10 | 8 | | 11 | 4 | | 12 | 48 | | 13 | 29 | | 14 | 9 | | 15 | 2 | | 16 | 6 | | 17 | 24 | | 18 | 6 | | 19 | 21 | | 20 | 2 | | 21 | 9 | | 22 | 7 | | 23 | 15 | | 24 | 17 | | 25 | 20 | | 26 | 14 | | 27 | 12 | | 28 | 4 | | 29 | 23 | | 30 | 59 | | 31 | 9 | | 32 | 29 | | 33 | 8 | | 34 | 38 | | 35 | 3 | | 36 | 5 | | 37 | 6 | | 38 | 41 | | 39 | 4 | | 40 | 8 | | 41 | 26 | | 42 | 17 | | 43 | 8 | | 44 | 53 | | 45 | 4 | | 46 | 10 | | 47 | 10 | | 48 | 7 | | 49 | 17 |
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| 82.62% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5212765957446809 | | totalSentences | 94 | | uniqueOpeners | 49 | |
| 93.90% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 71 | | matches | | 0 | "Of course he was." | | 1 | "Then she stood and faced" |
| | ratio | 0.028 | |
| 73.52% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 71 | | matches | | 0 | "You learned more in the" | | 1 | "She crouched and ran two" | | 2 | "They came away grey but" | | 3 | "He was good-looking in a" | | 4 | "His face was lean, grey-stubbled," | | 5 | "He wore a long oilcloth" | | 6 | "She crouched at the trench's" | | 7 | "She glanced up at him" | | 8 | "She had seen prints like" | | 9 | "She had told herself then" | | 10 | "She had told herself a" | | 11 | "she said evenly" | | 12 | "He came to the edge," | | 13 | "He pointed at the dead" | | 14 | "She looked at him for" | | 15 | "He wasn't lying." | | 16 | "He genuinely could not see" | | 17 | "She always had." | | 18 | "She crouched again and, with" | | 19 | "It was pointing at the" |
| | ratio | 0.366 | |
| 65.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 71 | | matches | | 0 | "The stairwell smelled of rust" | | 1 | "The old Tube station had" | | 2 | "Camden Borough Council had it" | | 3 | "A young constable steadied a" | | 4 | "The platform opened out before" | | 5 | "The tracks below the platform" | | 6 | "The constable hesitated" | | 7 | "Quinn adjusted the worn leather" | | 8 | "You learned more in the" | | 9 | "This one was already saying" | | 10 | "That was the first wrong" | | 11 | "A station sealed for fifty" | | 12 | "She crouched and ran two" | | 13 | "They came away grey but" | | 14 | "Someone had used this place," | | 15 | "He was good-looking in a" | | 16 | "Reyes pulled the tent flap" | | 17 | "Quinn stepped past him and" | | 18 | "The man lay on his" | | 19 | "His face was lean, grey-stubbled," |
| | ratio | 0.789 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 59.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 5 | | matches | | 0 | "The old Tube station had been sealed since the seventies — she'd checked the records on the drive over, because checking records was the kind of thing that kept…" | | 1 | "He was good-looking in a tired way, the sort of detective who closed cases by being likeable in interview rooms." | | 2 | "He wore a long oilcloth coat, good boots, a knitted scarf — not the layers of a rough sleeper, but the deliberate dress of someone who'd chosen to come somewher…" | | 3 | "It was pointing at the black mouth of the tunnel, trembling, as though something down there was pulling it." | | 4 | "There was a name forming at the edge of her mind, a name she'd been avoiding for three years, a young woman with an Oxford degree and a satchel full of books wh…" |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "she said quietly, more to herself than to Reyes" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.129 | | leniency | 0.258 | | rawRatio | 0 | | effectiveRatio | 0 | |