| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 80.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1041 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slowly" | | 1 | "suddenly" | | 2 | "very" | | 3 | "really" |
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| 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) | |
| 47.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1041 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "flickered" | | 1 | "echo" | | 2 | "pulsed" | | 3 | "sentinel" | | 4 | "flicker" |
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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 | 120 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 120 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 125 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 25 | | totalWords | 1041 | | ratio | 0.024 | | matches | | 0 | "from here, walk" | | 1 | "Fine. Acoustics. Fine." | | 2 | "just find the stones, Rory, please, I wouldn't ask if" | | 3 | "Near a Hel portal." | | 4 | "hello" | | 5 | "One two three four." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 1027 | | uniqueNames | 9 | | maxNameDensity | 0.78 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Eva" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Shoreditch | 1 | | Eva | 7 | | Rory | 8 | | Hel | 1 | | Pre-Law | 1 | | November | 1 | | Hoping | 1 |
| | persons | | | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Hel" | | 3 | "November" |
| | globalScore | 1 | | windowScore | 1 | |
| 25.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like a child's warning scrawled on" | | 1 | "seemed duller here, the batteries suddenly older" | | 2 | "something like one, long and pale and smooth" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1041 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 125 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 22.63 | | std | 20.88 | | cv | 0.923 | | sampleLengths | | 0 | 9 | | 1 | 50 | | 2 | 1 | | 3 | 52 | | 4 | 10 | | 5 | 56 | | 6 | 3 | | 7 | 66 | | 8 | 10 | | 9 | 56 | | 10 | 7 | | 11 | 31 | | 12 | 1 | | 13 | 38 | | 14 | 38 | | 15 | 8 | | 16 | 1 | | 17 | 20 | | 18 | 68 | | 19 | 26 | | 20 | 38 | | 21 | 7 | | 22 | 1 | | 23 | 16 | | 24 | 8 | | 25 | 48 | | 26 | 6 | | 27 | 18 | | 28 | 42 | | 29 | 17 | | 30 | 41 | | 31 | 5 | | 32 | 4 | | 33 | 19 | | 34 | 3 | | 35 | 44 | | 36 | 4 | | 37 | 15 | | 38 | 9 | | 39 | 1 | | 40 | 64 | | 41 | 9 | | 42 | 11 | | 43 | 51 | | 44 | 6 | | 45 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 120 | | matches | | |
| 12.73% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 178 | | matches | | 0 | "was matching" | | 1 | "was breathing" | | 2 | "wasn't looking" | | 3 | "were slowly giving" | | 4 | "was listening" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 125 | | ratio | 0 | | matches | (empty) | |
| 95.23% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1034 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 47 | | adverbRatio | 0.045454545454545456 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.010638297872340425 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 125 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 125 | | mean | 8.33 | | std | 8.13 | | cv | 0.976 | | sampleLengths | | 0 | 9 | | 1 | 10 | | 2 | 16 | | 3 | 2 | | 4 | 2 | | 5 | 20 | | 6 | 1 | | 7 | 4 | | 8 | 11 | | 9 | 19 | | 10 | 6 | | 11 | 12 | | 12 | 10 | | 13 | 8 | | 14 | 5 | | 15 | 30 | | 16 | 2 | | 17 | 1 | | 18 | 4 | | 19 | 3 | | 20 | 3 | | 21 | 1 | | 22 | 1 | | 23 | 1 | | 24 | 9 | | 25 | 18 | | 26 | 39 | | 27 | 10 | | 28 | 9 | | 29 | 15 | | 30 | 32 | | 31 | 7 | | 32 | 4 | | 33 | 17 | | 34 | 5 | | 35 | 5 | | 36 | 1 | | 37 | 10 | | 38 | 20 | | 39 | 8 | | 40 | 3 | | 41 | 13 | | 42 | 4 | | 43 | 2 | | 44 | 16 | | 45 | 2 | | 46 | 2 | | 47 | 3 | | 48 | 1 | | 49 | 1 |
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| 57.87% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.4 | | totalSentences | 125 | | uniqueOpeners | 50 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 92 | | matches | | 0 | "Just her own pale face" | | 1 | "Somewhere to her left, a" | | 2 | "Too tall for a fox." | | 3 | "Too quiet for a deer." | | 4 | "Just the flowers nodding at" | | 5 | "Then, at the far edge" | | 6 | "Near enough now that she" |
| | ratio | 0.076 | |
| 80.87% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 92 | | matches | | 0 | "She killed the engine." | | 1 | "She'd parked on the verge" | | 2 | "She started walking." | | 3 | "It started walking." | | 4 | "Her torch carved a narrow" | | 5 | "She thought of Eva's voice" | | 6 | "She pressed a hand over" | | 7 | "She clamped her teeth together" | | 8 | "She noticed that now." | | 9 | "She counted her steps to" | | 10 | "It rose out of the" | | 11 | "Her torch slid over the" | | 12 | "They moved when she wasn't" | | 13 | "She was almost sure." | | 14 | "They formed a rough ring," | | 15 | "They glowed faintly in the" | | 16 | "Her voice dropped into the" | | 17 | "She stepped between two of" | | 18 | "Her own breathing came back" | | 19 | "She shook it." |
| | ratio | 0.348 | |
| 79.57% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 92 | | matches | | 0 | "The sat-nav died at the" | | 1 | "Rory tapped the screen twice," | | 2 | "The little blue arrow that" | | 3 | "She killed the engine." | | 4 | "The ticking of cooling metal" | | 5 | "She'd parked on the verge" | | 6 | "Eva's handwriting usually made her" | | 7 | "Tonight it looked like a" | | 8 | "Rory zipped her jacket to" | | 9 | "The gravel under her boots" | | 10 | "That was the first thing." | | 11 | "A single footstep should not" | | 12 | "The echo stopped too." | | 13 | "She started walking." | | 14 | "It started walking." | | 15 | "Her torch carved a narrow" | | 16 | "Oak trees leaned over the" | | 17 | "She thought of Eva's voice" | | 18 | "The pendant against her sternum" | | 19 | "She pressed a hand over" |
| | ratio | 0.761 | |
| 54.35% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 92 | | matches | | | ratio | 0.011 | |
| 89.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 3 | | matches | | 0 | "The little blue arrow that had guided her from Shoreditch flickered, stuttered, and gave up entirely." | | 1 | "A single footstep should not echo in open parkland, and yet every crunch came back to her twice, as if somebody behind her was matching her stride a half-beat l…" | | 2 | "The whole world muffled, as though someone had pressed cotton wool against her ears." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |