| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.394 | | leniency | 0.788 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1269 | | totalAiIsmAdverbs | 1 | | 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) | |
| 84.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1269 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "stomach" | | 1 | "echoed" | | 2 | "charged" | | 3 | "throbbed" |
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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 | 91 | | matches | (empty) | |
| 95.76% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 91 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 14 | | totalWords | 1275 | | ratio | 0.011 | | matches | | 0 | "for" | | 1 | "the market, Harlow, they move it every month, you have to have a—" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 1065 | | uniqueNames | 13 | | maxNameDensity | 0.85 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Detective | 1 | | Harlow | 2 | | Quinn | 9 | | Tomás | 2 | | Herrera | 4 | | Saint | 1 | | Christopher | 1 | | Static | 1 | | Morris | 2 | | Buck | 1 | | Street | 1 | | English | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Static" | | 7 | "Morris" | | 8 | "Buck" | | 9 | "Street" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1275 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 110 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 23.61 | | std | 19.97 | | cv | 0.846 | | sampleLengths | | 0 | 23 | | 1 | 49 | | 2 | 26 | | 3 | 16 | | 4 | 3 | | 5 | 43 | | 6 | 37 | | 7 | 7 | | 8 | 43 | | 9 | 12 | | 10 | 57 | | 11 | 12 | | 12 | 2 | | 13 | 66 | | 14 | 39 | | 15 | 4 | | 16 | 39 | | 17 | 21 | | 18 | 33 | | 19 | 5 | | 20 | 63 | | 21 | 37 | | 22 | 13 | | 23 | 1 | | 24 | 20 | | 25 | 12 | | 26 | 21 | | 27 | 8 | | 28 | 108 | | 29 | 19 | | 30 | 21 | | 31 | 39 | | 32 | 7 | | 33 | 6 | | 34 | 33 | | 35 | 26 | | 36 | 27 | | 37 | 18 | | 38 | 4 | | 39 | 28 | | 40 | 25 | | 41 | 33 | | 42 | 4 | | 43 | 21 | | 44 | 24 | | 45 | 9 | | 46 | 3 | | 47 | 6 | | 48 | 30 | | 49 | 14 |
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| 89.84% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 91 | | matches | | 0 | "was gone" | | 1 | "being chased" | | 2 | "been bricked" | | 3 | "being tuned" |
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| 88.89% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 180 | | matches | | 0 | "were doing" | | 1 | "were playing" | | 2 | "was running" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 110 | | ratio | 0.055 | | matches | | 0 | "Long enough for her to see his face in the wash of a shop window — wide-eyed, mouth open, and not afraid of her at all." | | 1 | "She thought about it sometimes at the strangest moments — the way the mind reaches for solid ground." | | 2 | "Underneath the hiss, faintly, she heard something that was not English and not any language she recognised — a low murmuring, many voices, like a crowd heard through a wall." | | 3 | "Her voice went along the passage and came back wrong — a beat too late, and in a different pitch." | | 4 | "Lamps hung from cabling strung across the vaulted ceiling, and they burned in colours she had no words for — one of them shed light that made her hands look like they belonged to somebody else." | | 5 | "In the hospital, before the end, with the tube in his throat and his fingers scratching at her palm — *the market, Harlow, they move it every month, you have to have a—*" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1060 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.029245283018867925 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0047169811320754715 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 11.59 | | std | 9.1 | | cv | 0.785 | | sampleLengths | | 0 | 23 | | 1 | 15 | | 2 | 12 | | 3 | 22 | | 4 | 13 | | 5 | 13 | | 6 | 3 | | 7 | 6 | | 8 | 7 | | 9 | 3 | | 10 | 18 | | 11 | 5 | | 12 | 20 | | 13 | 3 | | 14 | 4 | | 15 | 22 | | 16 | 8 | | 17 | 7 | | 18 | 12 | | 19 | 31 | | 20 | 3 | | 21 | 9 | | 22 | 3 | | 23 | 2 | | 24 | 26 | | 25 | 3 | | 26 | 23 | | 27 | 9 | | 28 | 3 | | 29 | 2 | | 30 | 26 | | 31 | 12 | | 32 | 10 | | 33 | 18 | | 34 | 18 | | 35 | 13 | | 36 | 8 | | 37 | 4 | | 38 | 2 | | 39 | 8 | | 40 | 29 | | 41 | 3 | | 42 | 18 | | 43 | 3 | | 44 | 30 | | 45 | 5 | | 46 | 3 | | 47 | 24 | | 48 | 3 | | 49 | 16 |
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| 82.12% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.509090909090909 | | totalSentences | 110 | | uniqueOpeners | 56 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 80 | | matches | | 0 | "Then a voice, thin and" | | 1 | "Somewhere below, a stringed instrument" | | 2 | "Somewhere below, past the lamps" |
| | ratio | 0.038 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 80 | | matches | | 0 | "He landed badly, stumbled, caught" | | 1 | "She hit the alley at" | | 2 | "Her hip took the wall." | | 3 | "He was quick." | | 4 | "She'd give him that." | | 5 | "He came out of the" | | 6 | "He looked back." | | 7 | "She'd seen that look before," | | 8 | "His accent thickened when he" | | 9 | "He turned into the lock" | | 10 | "Her watch strap had soaked" | | 11 | "She'd bought that watch the" | | 12 | "She thought about it sometimes" | | 13 | "She wiped it on her" | | 14 | "She turned the radio off." | | 15 | "It went warm and dry" | | 16 | "Her voice went along the" | | 17 | "She kept walking." | | 18 | "Her right hand found the" | | 19 | "She hated how her voice" |
| | ratio | 0.288 | |
| 78.75% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 80 | | matches | | 0 | "Rain came off the Camden" | | 1 | "He landed badly, stumbled, caught" | | 2 | "The Saint Christopher on his" | | 3 | "Quinn said into her shoulder" | | 4 | "Static answered her." | | 5 | "She hit the alley at" | | 6 | "Her hip took the wall." | | 7 | "Pain flowered along her ribs," | | 8 | "He was quick." | | 9 | "She'd give him that." | | 10 | "Herrera ran like a man" | | 11 | "That was the part that" | | 12 | "He came out of the" | | 13 | "A night bus blared its" | | 14 | "He looked back." | | 15 | "She'd seen that look before," | | 16 | "His accent thickened when he" | | 17 | "He turned into the lock" | | 18 | "Her watch strap had soaked" | | 19 | "She'd bought that watch the" |
| | ratio | 0.763 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 2 | | matches | | 0 | "A night bus blared its horn and swerved, spray fanning up over the kerb, and Quinn went through the wake of it with water in her mouth and her eyes stinging." | | 1 | "Underneath the hiss, faintly, she heard something that was not English and not any language she recognised — a low murmuring, many voices, like a crowd heard th…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 33 | | tagDensity | 0.242 | | leniency | 0.485 | | rawRatio | 0.125 | | effectiveRatio | 0.061 | |