| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.24 | | leniency | 0.48 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1465 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 93.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1465 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 0 | | narrationSentences | 74 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 112 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 93 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1478 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 64.05% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 989 | | uniqueNames | 7 | | maxNameDensity | 1.72 | | worstName | "Silas" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Silas | 17 | | Aurora | 14 | | Armagnac | 3 | | Peter | 8 | | Soho | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Aurora" | | 4 | "Peter" |
| | places | | | globalScore | 0.641 | | windowScore | 0.833 | |
| 47.96% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a drowned man, and then like" | | 1 | "something close to fondness" |
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| 64.68% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.353 | | wordCount | 1478 | | matches | | 0 | "not anger, not grief, but the exhaustion of a man who had been holding a door shut for" | | 1 | "not grief, but the exhaustion of a man who had been holding a door shut for" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 112 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 65 | | mean | 22.74 | | std | 23.06 | | cv | 1.014 | | sampleLengths | | 0 | 91 | | 1 | 13 | | 2 | 48 | | 3 | 12 | | 4 | 2 | | 5 | 3 | | 6 | 38 | | 7 | 37 | | 8 | 2 | | 9 | 8 | | 10 | 31 | | 11 | 12 | | 12 | 1 | | 13 | 25 | | 14 | 35 | | 15 | 3 | | 16 | 12 | | 17 | 8 | | 18 | 27 | | 19 | 55 | | 20 | 14 | | 21 | 5 | | 22 | 6 | | 23 | 28 | | 24 | 12 | | 25 | 10 | | 26 | 13 | | 27 | 60 | | 28 | 7 | | 29 | 125 | | 30 | 50 | | 31 | 5 | | 32 | 2 | | 33 | 4 | | 34 | 27 | | 35 | 65 | | 36 | 5 | | 37 | 7 | | 38 | 45 | | 39 | 26 | | 40 | 50 | | 41 | 32 | | 42 | 3 | | 43 | 5 | | 44 | 2 | | 45 | 15 | | 46 | 10 | | 47 | 3 | | 48 | 1 | | 49 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 74 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 164 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 1 | | flaggedSentences | 9 | | totalSentences | 112 | | ratio | 0.08 | | matches | | 0 | "The last regular left a little after ten, collar up against the rain, and the Raven's Nest settled into its late quiet — the hum of the green neon above the door, the tick of the glass washer, water combing the pavement outside." | | 1 | "Tall once, perhaps — now the coat wore him, good cloth gone thin at the shoulders, white hair plastered to a skull that had outgrown its face." | | 2 | "Then he reached under the counter and brought up a bottle Aurora had never seen — Armagnac, its label the colour of weak tea — and poured two fingers." | | 3 | "The wet weather had his left leg stiff; Aurora could see it in the way he kept his weight off it, a geometry she knew by now." | | 4 | "The man's gaze wandered the walls — the old maps, the black-and-white photographs in their dark frames — and stopped where Aurora knew it would." | | 5 | "\"The signal was burnt.\" Peter's voice dropped into a register that had been rehearsed, Aurora realised — rehearsed for thirty years, in cars, in showers, in the hour before dawn." | | 6 | "Silas looked at him then, full on, and Aurora saw something she had never seen in him — not anger, not grief, but the exhaustion of a man who had been holding a door shut for three decades and had forgotten what was behind it." | | 7 | "His gaze drifted to Aurora at the end of the bar and stayed a beat too long — the dark hair, the stillness of her — and something moved behind his face." | | 8 | "The photographs kept their own counsel on the walls — tram lines, a street corner, a woman mid-laugh, forever half-turned away." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 583 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.018867924528301886 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 112 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 112 | | mean | 13.2 | | std | 13.7 | | cv | 1.038 | | sampleLengths | | 0 | 43 | | 1 | 29 | | 2 | 19 | | 3 | 13 | | 4 | 10 | | 5 | 27 | | 6 | 10 | | 7 | 1 | | 8 | 4 | | 9 | 8 | | 10 | 2 | | 11 | 3 | | 12 | 14 | | 13 | 24 | | 14 | 8 | | 15 | 29 | | 16 | 2 | | 17 | 8 | | 18 | 8 | | 19 | 3 | | 20 | 20 | | 21 | 12 | | 22 | 1 | | 23 | 25 | | 24 | 8 | | 25 | 27 | | 26 | 3 | | 27 | 12 | | 28 | 8 | | 29 | 3 | | 30 | 24 | | 31 | 25 | | 32 | 1 | | 33 | 16 | | 34 | 2 | | 35 | 11 | | 36 | 7 | | 37 | 7 | | 38 | 5 | | 39 | 6 | | 40 | 10 | | 41 | 18 | | 42 | 12 | | 43 | 7 | | 44 | 3 | | 45 | 4 | | 46 | 9 | | 47 | 26 | | 48 | 34 | | 49 | 2 |
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| 70.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.42857142857142855 | | totalSentences | 112 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 62 | | matches | | 0 | "Then he reached under the" | | 1 | "Somewhere upstairs a pipe knocked" | | 2 | "Then the door opened, closed," |
| | ratio | 0.048 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 62 | | matches | | 0 | "He stood on the mat" | | 1 | "He looked at Silas the" | | 2 | "He crossed the room with" | | 3 | "His fingers had a tremor" | | 4 | "His right hand found the" | | 5 | "He said it the way" | | 6 | "Her thumb found the small" | | 7 | "His gaze drifted to Aurora" | | 8 | "He looked down at the" | | 9 | "He buttoned the thin coat" | | 10 | "She slid off the stool" | | 11 | "He almost smiled." | | 12 | "It didn't reach anywhere, but" | | 13 | "She flipped the sign to" |
| | ratio | 0.226 | |
| 32.58% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 53 | | totalSentences | 62 | | matches | | 0 | "The last regular left a" | | 1 | "Aurora sat at the far" | | 2 | "The door opened and let" | | 3 | "He stood on the mat" | | 4 | "He looked at Silas the" | | 5 | "The cloth stopped mid-circle." | | 6 | "Silas set the glass down" | | 7 | "The voice had an education" | | 8 | "He crossed the room with" | | 9 | "Silas looked at him for" | | 10 | "The man wrapped his hand" | | 11 | "His fingers had a tremor" | | 12 | "Silas leaned his hip against" | | 13 | "The wet weather had his" | | 14 | "Silas said nothing." | | 15 | "His right hand found the" | | 16 | "The man's gaze wandered the" | | 17 | "A street corner, tram lines," | | 18 | "Aurora had dusted that frame" | | 19 | "the man said" |
| | ratio | 0.855 | |
| 80.65% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 62 | | matches | | | ratio | 0.016 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 2 | | matches | | 0 | "Tall once, perhaps — now the coat wore him, good cloth gone thin at the shoulders, white hair plastered to a skull that had outgrown its face." | | 1 | "Silas looked at him then, full on, and Aurora saw something she had never seen in him — not anger, not grief, but the exhaustion of a man who had been holding a…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.14 | | leniency | 0.28 | | rawRatio | 0 | | effectiveRatio | 0 | |