| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1527 | | 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) | |
| 41.06% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1527 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "chill" | | 1 | "warmth" | | 2 | "stark" | | 3 | "pulsed" | | 4 | "rhythmic" | | 5 | "echoing" | | 6 | "perfect" | | 7 | "vibrated" | | 8 | "flicked" | | 9 | "wavering" | | 10 | "weight" | | 11 | "throbbed" | | 12 | "fractured" | | 13 | "trembled" | | 14 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 282 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 282 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 282 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1527 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 97.61% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1527 | | uniqueNames | 9 | | maxNameDensity | 1.05 | | worstName | "You" | | maxWindowNameDensity | 2 | | worstWindowName | "You" | | discoveredNames | | Aurora | 1 | | Heartstone | 1 | | Richmond | 3 | | Peckham | 1 | | Hel | 1 | | Park | 1 | | Right | 3 | | You | 16 | | Rory | 7 |
| | persons | | | places | | 0 | "Aurora" | | 1 | "Richmond" | | 2 | "Peckham" | | 3 | "Park" |
| | globalScore | 0.976 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 104 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like a tongue peeling off a palate" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.655 | | wordCount | 1527 | | matches | | 0 | "Not a gradual chill, but a sudden vacuum" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 282 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 28.28 | | std | 22.52 | | cv | 0.796 | | sampleLengths | | 0 | 52 | | 1 | 12 | | 2 | 3 | | 3 | 12 | | 4 | 6 | | 5 | 46 | | 6 | 32 | | 7 | 16 | | 8 | 56 | | 9 | 6 | | 10 | 14 | | 11 | 40 | | 12 | 6 | | 13 | 43 | | 14 | 19 | | 15 | 59 | | 16 | 5 | | 17 | 40 | | 18 | 61 | | 19 | 9 | | 20 | 53 | | 21 | 7 | | 22 | 34 | | 23 | 9 | | 24 | 37 | | 25 | 5 | | 26 | 26 | | 27 | 1 | | 28 | 13 | | 29 | 10 | | 30 | 37 | | 31 | 49 | | 32 | 10 | | 33 | 45 | | 34 | 17 | | 35 | 8 | | 36 | 59 | | 37 | 5 | | 38 | 64 | | 39 | 8 | | 40 | 71 | | 41 | 48 | | 42 | 10 | | 43 | 69 | | 44 | 57 | | 45 | 8 | | 46 | 81 | | 47 | 19 | | 48 | 7 | | 49 | 38 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 282 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 301 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 282 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1528 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.01963350785340314 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0032722513089005235 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 282 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 282 | | mean | 5.41 | | std | 3.26 | | cv | 0.602 | | sampleLengths | | 0 | 7 | | 1 | 17 | | 2 | 5 | | 3 | 18 | | 4 | 5 | | 5 | 4 | | 6 | 8 | | 7 | 3 | | 8 | 8 | | 9 | 4 | | 10 | 6 | | 11 | 3 | | 12 | 15 | | 13 | 13 | | 14 | 5 | | 15 | 5 | | 16 | 5 | | 17 | 9 | | 18 | 5 | | 19 | 6 | | 20 | 4 | | 21 | 8 | | 22 | 8 | | 23 | 8 | | 24 | 8 | | 25 | 5 | | 26 | 13 | | 27 | 4 | | 28 | 1 | | 29 | 1 | | 30 | 1 | | 31 | 8 | | 32 | 15 | | 33 | 6 | | 34 | 2 | | 35 | 2 | | 36 | 4 | | 37 | 6 | | 38 | 5 | | 39 | 9 | | 40 | 7 | | 41 | 2 | | 42 | 17 | | 43 | 3 | | 44 | 3 | | 45 | 12 | | 46 | 4 | | 47 | 1 | | 48 | 4 | | 49 | 9 |
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| 30.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 54 | | diversityRatio | 0.20212765957446807 | | totalSentences | 282 | | uniqueOpeners | 57 | |
| 40.82% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 245 | | matches | | 0 | "Instead, they swayed without wind." | | 1 | "Then came the wet click." | | 2 | "Light bent around their edges." |
| | ratio | 0.012 | |
| 35.51% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 113 | | totalSentences | 245 | | matches | | 0 | "She adjusted the Heartstone pendant" | | 1 | "She checked her watch." | | 2 | "You led me out here" | | 3 | "She stepped past the boundary" | | 4 | "They should have been dormant." | | 5 | "They should have been dead." | | 6 | "She kept her hands free." | | 7 | "It matched a heartbeat that" | | 8 | "I followed the warmth from" | | 9 | "You do not get to" | | 10 | "She walked toward the centre" | | 11 | "She counted her steps." | | 12 | "It sounded like a tongue" | | 13 | "It came from behind her" | | 14 | "You want attention." | | 15 | "You have it." | | 16 | "She dropped to one knee" | | 17 | "It yielded like flesh." | | 18 | "She wiped her hand on" | | 19 | "She tracked the tree line." |
| | ratio | 0.461 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 227 | | totalSentences | 245 | | matches | | 0 | "The silver chain bit into" | | 1 | "She adjusted the Heartstone pendant" | | 2 | "Bark flaked under her fingers." | | 3 | "The standing stones rose from" | | 4 | "She checked her watch." | | 5 | "The second hand stuttered, jumped" | | 6 | "You led me out here" | | 7 | "She stepped past the boundary" | | 8 | "The temperature dropped." | | 9 | "Wildflowers carpeted the grass, their" | | 10 | "They should have been dormant." | | 11 | "They should have been dead." | | 12 | "Rory unbuttoned her coat and" | | 13 | "She kept her hands free." | | 14 | "The pendant pulsed against her" | | 15 | "A slow, rhythmic heat." | | 16 | "It matched a heartbeat that" | | 17 | "I followed the warmth from" | | 18 | "You do not get to" | | 19 | "She walked toward the centre" |
| | ratio | 0.927 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 245 | | matches | (empty) | | ratio | 0 | |
| 89.95% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 2 | | matches | | 0 | "The wildflowers bent in a perfect circle, as though something heavy had just risen from the soil." | | 1 | "A drawn-out exhale that shaped itself into something almost recognisable." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |