| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 1 | | adverbTags | | 0 | "She crouched again [again]" |
| | dialogueSentences | 37 | | tagDensity | 0.486 | | leniency | 0.973 | | rawRatio | 0.056 | | effectiveRatio | 0.054 | |
| 91.50% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1176 | | 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) | |
| 65.99% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1176 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "unsettled" | | 1 | "warmth" | | 2 | "etched" | | 3 | "aligned" | | 4 | "weight" | | 5 | "trembled" | | 6 | "quivered" |
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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 | 64 | | matches | (empty) | |
| 98.21% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 64 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 83 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1188 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 88.78% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 735 | | uniqueNames | 11 | | maxNameDensity | 1.22 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 9 | | Camden | 2 | | High | 1 | | Street | 1 | | Underground | 1 | | Theo | 1 | | Rennick | 6 | | Purple | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Theo" | | 3 | "Rennick" | | 4 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.888 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.842 | | wordCount | 1188 | | matches | | 0 | "not as a place, but as a sentence somebody else had written" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 33.94 | | std | 27.23 | | cv | 0.802 | | sampleLengths | | 0 | 11 | | 1 | 53 | | 2 | 80 | | 3 | 49 | | 4 | 2 | | 5 | 28 | | 6 | 49 | | 7 | 5 | | 8 | 39 | | 9 | 68 | | 10 | 7 | | 11 | 38 | | 12 | 4 | | 13 | 8 | | 14 | 49 | | 15 | 7 | | 16 | 74 | | 17 | 45 | | 18 | 4 | | 19 | 2 | | 20 | 60 | | 21 | 23 | | 22 | 28 | | 23 | 7 | | 24 | 86 | | 25 | 2 | | 26 | 82 | | 27 | 15 | | 28 | 3 | | 29 | 66 | | 30 | 26 | | 31 | 80 | | 32 | 26 | | 33 | 43 | | 34 | 19 |
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| 99.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 64 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 115 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 83 | | ratio | 0.072 | | matches | | 0 | "Now she stood on a platform that shouldn't exist — no map of the Underground she'd studied listed it — watching blue-white light from the forensic lamps catch on tile mosaics that depicted no station name, only symbols." | | 1 | "His shirt gaped open over a chest split from sternum to navel — a wound that should have painted the tiles for metres." | | 2 | "Rigor had come and gone — call it thirty hours dead." | | 3 | "\"There is.\" Quinn rose and turned in a slow circle, reading the platform the way she'd read every scene in eighteen years — not as a place, but as a sentence somebody else had written." | | 4 | "\"Bag everything. The bones, the grit from the body's outline, a core sample of that tile if the techs can manage it.\" Quinn checked her watch — the worn leather strap, the face she'd never replaced after Morris cracked it — and looked again toward the tunnel's dark." | | 5 | "Through the clear plastic, the brass sliver trembled against her glove, not north, never north — but fixed, insistent, toward the tunnel mouth." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 729 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.027434842249657063 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006858710562414266 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 83 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 83 | | mean | 14.31 | | std | 11.6 | | cv | 0.81 | | sampleLengths | | 0 | 11 | | 1 | 35 | | 2 | 8 | | 3 | 1 | | 4 | 9 | | 5 | 34 | | 6 | 38 | | 7 | 3 | | 8 | 5 | | 9 | 15 | | 10 | 19 | | 11 | 15 | | 12 | 2 | | 13 | 19 | | 14 | 9 | | 15 | 2 | | 16 | 16 | | 17 | 23 | | 18 | 8 | | 19 | 5 | | 20 | 17 | | 21 | 12 | | 22 | 10 | | 23 | 21 | | 24 | 10 | | 25 | 1 | | 26 | 36 | | 27 | 7 | | 28 | 32 | | 29 | 6 | | 30 | 4 | | 31 | 8 | | 32 | 14 | | 33 | 35 | | 34 | 7 | | 35 | 5 | | 36 | 41 | | 37 | 28 | | 38 | 25 | | 39 | 20 | | 40 | 4 | | 41 | 2 | | 42 | 10 | | 43 | 10 | | 44 | 11 | | 45 | 5 | | 46 | 24 | | 47 | 6 | | 48 | 2 | | 49 | 15 |
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| 84.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5301204819277109 | | totalSentences | 83 | | uniqueOpeners | 44 | |
| 62.89% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 53 | | matches | | 0 | "Somewhere down there, air moved." |
| | ratio | 0.019 | |
| 91.70% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 53 | | matches | | 0 | "They sat in a neat" | | 1 | "She'd entered through a maintenance" | | 2 | "He crouched over it with" | | 3 | "His shirt gaped open over" | | 4 | "He eased the body's shoulder" | | 5 | "He glanced up at the" | | 6 | "She crouched again and studied" | | 7 | "His voice dropped, the way" | | 8 | "She let the words sit" | | 9 | "She eased the fingers open." | | 10 | "She held it under the" | | 11 | "She walked to the platform's" | | 12 | "His face changed." | | 13 | "He kept his hand flat" | | 14 | "She'd felt it on her" | | 15 | "She looked down." | | 16 | "It had been still a" |
| | ratio | 0.321 | |
| 54.34% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 43 | | totalSentences | 53 | | matches | | 0 | "The bones were the first" | | 1 | "They sat in a neat" | | 2 | "Quinn had counted forty-seven before" | | 3 | "The body waited at the" | | 4 | "She'd entered through a maintenance" | | 5 | "DS Theo Rennick called from" | | 6 | "He crouched over it with" | | 7 | "Rennick tilted his head toward" | | 8 | "The victim lay spread on" | | 9 | "His shirt gaped open over" | | 10 | "The concrete around him gleamed" | | 11 | "He eased the body's shoulder" | | 12 | "Quinn lowered herself to one" | | 13 | "The tiles near the body" | | 14 | "The rest of the station" | | 15 | "He glanced up at the" | | 16 | "Quinn straightened and paced the" | | 17 | "Rennick opened his mouth, then" | | 18 | "She crouched again and studied" | | 19 | "His voice dropped, the way" |
| | ratio | 0.811 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 53 | | matches | | 0 | "Now she stood on a" | | 1 | "Now it quivered like a" |
| | ratio | 0.038 | |
| 18.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 4 | | matches | | 0 | "The bones were the first thing that bothered Detective Harlow Quinn." | | 1 | "Now she stood on a platform that shouldn't exist — no map of the Underground she'd studied listed it — watching blue-white light from the forensic lamps catch o…" | | 2 | "The rest of the station breathed cold enough to fog her breath, but a ring of warmth radiated outward from the corpse, perhaps half a metre, as if the stone rem…" | | 3 | "She'd felt it on her neck for the last ten minutes, a faint warm draught from a tunnel that should have been sealed and dead for decades." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 95.95% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "she continued (continue)" | | 1 | "he admitted (admit)" |
| | dialogueSentences | 37 | | tagDensity | 0.162 | | leniency | 0.324 | | rawRatio | 0.333 | | effectiveRatio | 0.108 | |