| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.22% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 865 | | 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) | |
| 71.10% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 865 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "could feel" | | 1 | "pulse" | | 2 | "flicker" | | 3 | "flicked" | | 4 | "electric" |
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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 | 55 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 55 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 62 | | 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 | 3 | | markdownWords | 12 | | totalWords | 865 | | ratio | 0.014 | | matches | | 0 | "unexplained" | | 1 | "no further lines of inquiry" | | 2 | "Quinn, you won't believe what the" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 747 | | uniqueNames | 20 | | maxNameDensity | 0.67 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Mornington | 1 | | Crescent | 1 | | Harlow | 1 | | Quinn | 5 | | Camden | 2 | | High | 1 | | Street | 1 | | Herrera | 3 | | General | 1 | | Medical | 1 | | Council | 1 | | St | 1 | | Christopher | 1 | | Victorian | 1 | | Underground | 1 | | Town | 1 | | London | 1 | | Spanish | 1 | | Morris | 3 | | Hackney | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Council" | | 4 | "Morris" |
| | places | | 0 | "Mornington" | | 1 | "Crescent" | | 2 | "Camden" | | 3 | "High" | | 4 | "Street" | | 5 | "St" | | 6 | "Christopher" | | 7 | "Town" | | 8 | "London" | | 9 | "Hackney" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 37 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 84.39% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.156 | | wordCount | 865 | | matches | | 0 | "not panic, but calculation" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 62 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 34.6 | | std | 26.61 | | cv | 0.769 | | sampleLengths | | 0 | 62 | | 1 | 77 | | 2 | 5 | | 3 | 45 | | 4 | 66 | | 5 | 56 | | 6 | 12 | | 7 | 56 | | 8 | 29 | | 9 | 8 | | 10 | 7 | | 11 | 106 | | 12 | 6 | | 13 | 6 | | 14 | 55 | | 15 | 4 | | 16 | 31 | | 17 | 43 | | 18 | 9 | | 19 | 52 | | 20 | 17 | | 21 | 17 | | 22 | 42 | | 23 | 40 | | 24 | 14 |
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| 86.12% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 55 | | matches | | 0 | "been peeled" | | 1 | "was softened" | | 2 | "was gone" |
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| 38.71% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 124 | | matches | | 0 | "was running" | | 1 | "was chasing" | | 2 | "was heading" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 62 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 748 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.026737967914438502 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.00267379679144385 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 62 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 62 | | mean | 13.95 | | std | 12.61 | | cv | 0.904 | | sampleLengths | | 0 | 36 | | 1 | 3 | | 2 | 23 | | 3 | 21 | | 4 | 2 | | 5 | 38 | | 6 | 9 | | 7 | 7 | | 8 | 5 | | 9 | 3 | | 10 | 16 | | 11 | 26 | | 12 | 4 | | 13 | 3 | | 14 | 59 | | 15 | 16 | | 16 | 2 | | 17 | 5 | | 18 | 33 | | 19 | 2 | | 20 | 4 | | 21 | 6 | | 22 | 5 | | 23 | 9 | | 24 | 29 | | 25 | 7 | | 26 | 6 | | 27 | 10 | | 28 | 15 | | 29 | 4 | | 30 | 8 | | 31 | 7 | | 32 | 4 | | 33 | 16 | | 34 | 55 | | 35 | 11 | | 36 | 3 | | 37 | 17 | | 38 | 6 | | 39 | 6 | | 40 | 3 | | 41 | 21 | | 42 | 31 | | 43 | 4 | | 44 | 7 | | 45 | 20 | | 46 | 4 | | 47 | 11 | | 48 | 32 | | 49 | 9 |
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| 84.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5483870967741935 | | totalSentences | 62 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 50 | | matches | | 0 | "Then it was gone." | | 1 | "Somewhere far below, a crowd" |
| | ratio | 0.04 | |
| 76.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 50 | | matches | | 0 | "She ignored it." | | 1 | "Her left wrist was slick" | | 2 | "He glanced back." | | 3 | "He lifted a hand to" | | 4 | "Her knee complained." | | 5 | "She stopped at the gate." | | 6 | "He had squeezed through a" | | 7 | "His accent was softened by" | | 8 | "She had some idea." | | 9 | "She had three years of" | | 10 | "He tapped the iron bars" | | 11 | "he said, and he meant" | | 12 | "He turned and walked away" | | 13 | "She thought of Morris, his" | | 14 | "She thought of the watch" | | 15 | "She turned sideways and forced" | | 16 | "Her boots hit wet tile." | | 17 | "She straightened, drew a breath" |
| | ratio | 0.36 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 35 | | totalSentences | 50 | | matches | | 0 | "The rain had come on" | | 1 | "She ignored it." | | 2 | "Her left wrist was slick" | | 3 | "The people who didn't show" | | 4 | "The people who bled a" | | 5 | "He glanced back." | | 6 | "He lifted a hand to" | | 7 | "Quinn sprinted after him." | | 8 | "Her knee complained." | | 9 | "The road ran downhill, out" | | 10 | "A sign so weathered she" | | 11 | "She stopped at the gate." | | 12 | "Herrera was already on the" | | 13 | "He had squeezed through a" | | 14 | "His accent was softened by" | | 15 | "She had some idea." | | 16 | "She had three years of" | | 17 | "Morris had never been the" | | 18 | "Neither had she." | | 19 | "The thread, it seemed, ran" |
| | ratio | 0.7 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 50 | | matches | | 0 | "Even through the rain and" |
| | ratio | 0.02 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 4 | | matches | | 0 | "Twenty-nine years old, a paramedic until the General Medical Council had taken his licence, and now, according to three separate informants and one very frighte…" | | 1 | "Eighteen years of service had taught her a great many things about pursuit, chiefly that the man who knew the terrain always won, and she had no idea what terra…" | | 2 | "Every instinct she'd built over eighteen years, every hard lesson about backup, procedure, and not going in blind, screamed at her to step back, radio in, wait …" | | 3 | "Below her, the stairs spiralled down into a light that was not electric, pale and shifting, the colour of moonlight through dirty glass." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0 | | effectiveRatio | 0 | |