| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 39 | | tagDensity | 0.436 | | leniency | 0.872 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1172 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 95.73% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1172 | | totalAiIsms | 1 | | 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 | 0 | | hedgeCount | 0 | | narrationSentences | 74 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1178 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 94.81% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 906 | | uniqueNames | 7 | | maxNameDensity | 1.1 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Pryce" | | discoveredNames | | Dry | 1 | | Attlee | 1 | | Pryce | 8 | | Quinn | 10 | | Twelve | 1 | | Whitechapel | 1 | | Morris | 1 |
| | persons | | 0 | "Pryce" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | | globalScore | 0.948 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.849 | | wordCount | 1178 | | matches | | 0 | "not fading the way prints fade, but ending" |
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| 96.49% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 95 | | matches | | 0 | "past that edge" | | 1 | "cloven that Quinn" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 25.61 | | std | 24.6 | | cv | 0.961 | | sampleLengths | | 0 | 59 | | 1 | 10 | | 2 | 45 | | 3 | 11 | | 4 | 73 | | 5 | 20 | | 6 | 3 | | 7 | 24 | | 8 | 9 | | 9 | 63 | | 10 | 3 | | 11 | 45 | | 12 | 3 | | 13 | 4 | | 14 | 65 | | 15 | 20 | | 16 | 12 | | 17 | 15 | | 18 | 47 | | 19 | 5 | | 20 | 13 | | 21 | 68 | | 22 | 7 | | 23 | 3 | | 24 | 1 | | 25 | 84 | | 26 | 12 | | 27 | 4 | | 28 | 33 | | 29 | 47 | | 30 | 5 | | 31 | 6 | | 32 | 2 | | 33 | 8 | | 34 | 66 | | 35 | 47 | | 36 | 2 | | 37 | 32 | | 38 | 46 | | 39 | 3 | | 40 | 43 | | 41 | 30 | | 42 | 4 | | 43 | 4 | | 44 | 4 | | 45 | 68 |
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| 95.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 74 | | matches | | 0 | "was scoured" | | 1 | "been touched" |
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| 58.16% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 141 | | matches | | 0 | "wasn't pointing" | | 1 | "was swinging" | | 2 | "was waiting" |
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| 22.56% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 95 | | ratio | 0.042 | | matches | | 0 | "Quinn took it slow, one hand off the rail, her torch beam sliding over tiles the colour of weak tea, and counted the steps out of habit — forty-two down to the platform, the last six slick enough that the uniform ahead of her went down on one knee and swore." | | 1 | "His eyes were open too, and white — not rolled back, not clouded — white the way frosted glass is white, edge to edge, no iris at all." | | 2 | "It ran up against a straight edge and stopped, and past that edge the concrete was scoured clean — not swept, scoured, in a rectangle maybe six feet by four, its corners crisp as a cut." | | 3 | "Protective marks scratched around the face in a ring — she recognised the shapes without knowing why, and that bothered her more than the eyes did." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 513 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.01949317738791423 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.001949317738791423 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 12.4 | | std | 11.09 | | cv | 0.894 | | sampleLengths | | 0 | 8 | | 1 | 51 | | 2 | 10 | | 3 | 14 | | 4 | 3 | | 5 | 15 | | 6 | 13 | | 7 | 11 | | 8 | 21 | | 9 | 52 | | 10 | 5 | | 11 | 15 | | 12 | 3 | | 13 | 19 | | 14 | 5 | | 15 | 9 | | 16 | 17 | | 17 | 14 | | 18 | 4 | | 19 | 28 | | 20 | 3 | | 21 | 7 | | 22 | 38 | | 23 | 3 | | 24 | 4 | | 25 | 13 | | 26 | 33 | | 27 | 13 | | 28 | 6 | | 29 | 3 | | 30 | 17 | | 31 | 7 | | 32 | 5 | | 33 | 11 | | 34 | 4 | | 35 | 21 | | 36 | 2 | | 37 | 2 | | 38 | 10 | | 39 | 12 | | 40 | 5 | | 41 | 13 | | 42 | 9 | | 43 | 36 | | 44 | 3 | | 45 | 2 | | 46 | 18 | | 47 | 7 | | 48 | 3 | | 49 | 1 |
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| 95.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.6105263157894737 | | totalSentences | 95 | | uniqueOpeners | 58 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 60 | | matches | | 0 | "She ran her thumb along" | | 1 | "He didn't look up" | | 2 | "His mouth was open." | | 3 | "His eyes were open too," | | 4 | "She lifted the man's right" | | 5 | "She set it down" | | 6 | "She swung the beam wide," | | 7 | "It ran up against a" | | 8 | "She moved along the row," | | 9 | "She smelled her fingertip." | | 10 | "He took nearly a minute." | | 11 | "They came off the stairwell" | | 12 | "She stood at that line" | | 13 | "He came over with an" | | 14 | "He held up the bag" | | 15 | "It was swinging in slow," | | 16 | "He shut his mouth." |
| | ratio | 0.283 | |
| 76.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 60 | | matches | | 0 | "The stairwell smelled of iron" | | 1 | "Quinn took it slow, one" | | 2 | "Quinn stopped, crouched, pressed two" | | 3 | "She ran her thumb along" | | 4 | "The constable had no answer," | | 5 | "The platform opened out ahead" | | 6 | "Somebody had rigged two work" | | 7 | "He didn't look up" | | 8 | "Pryce finally raised his eyes" | | 9 | "Quinn came the last twenty" | | 10 | "The man lay on his" | | 11 | "Fifties, maybe older, grey stubble," | | 12 | "His mouth was open." | | 13 | "His eyes were open too," | | 14 | "Pryce had his notebook out" | | 15 | "Quinn lowered herself onto her" | | 16 | "She lifted the man's right" | | 17 | "She set it down" | | 18 | "Pryce leaned in." | | 19 | "Quinn shone the torch along" |
| | ratio | 0.767 | |
| 83.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 60 | | matches | | 0 | "To his credit, when he" |
| | ratio | 0.017 | |
| 73.73% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 3 | | matches | | 0 | "Sugar, burnt, with something under it that made the back of her throat itch, like the air after a substation goes." | | 1 | "The cold came off the tunnel mouth in a slow breath, and she thought about a stairwell in Whitechapel three years ago and Morris's voice going flat mid-sentence…" | | 2 | "A disc of something yellowed and porous, drilled off-centre, its face cut with a mark like a knot that doubled back on itself." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 39 | | tagDensity | 0.128 | | leniency | 0.256 | | rawRatio | 0 | | effectiveRatio | 0 | |