| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1436 | | 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) | |
| 65.18% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1436 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "silk" | | 1 | "pulsed" | | 2 | "footsteps" | | 3 | "pulse" | | 4 | "warmth" | | 5 | "weight" | | 6 | "perfect" | | 7 | "flicked" | | 8 | "chill" |
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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 | 1 | | narrationSentences | 137 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 137 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 158 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1439 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 65.80% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1247 | | uniqueNames | 10 | | maxNameDensity | 1.68 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 2 | | Park | 1 | | Rory | 21 | | London | 1 | | September | 1 | | English | 1 | | Nyx | 10 | | Heartstone | 1 | | Isolde | 5 | | Pollen | 3 |
| | persons | | 0 | "Rory" | | 1 | "Nyx" | | 2 | "Isolde" | | 3 | "Pollen" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" |
| | globalScore | 0.658 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 92 | | 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 | 1439 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 158 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 23.21 | | std | 21.04 | | cv | 0.907 | | sampleLengths | | 0 | 13 | | 1 | 54 | | 2 | 36 | | 3 | 15 | | 4 | 3 | | 5 | 44 | | 6 | 10 | | 7 | 3 | | 8 | 3 | | 9 | 79 | | 10 | 31 | | 11 | 1 | | 12 | 52 | | 13 | 4 | | 14 | 66 | | 15 | 18 | | 16 | 10 | | 17 | 27 | | 18 | 1 | | 19 | 2 | | 20 | 76 | | 21 | 7 | | 22 | 3 | | 23 | 43 | | 24 | 67 | | 25 | 16 | | 26 | 4 | | 27 | 14 | | 28 | 8 | | 29 | 66 | | 30 | 2 | | 31 | 12 | | 32 | 14 | | 33 | 9 | | 34 | 9 | | 35 | 2 | | 36 | 43 | | 37 | 3 | | 38 | 52 | | 39 | 10 | | 40 | 58 | | 41 | 19 | | 42 | 11 | | 43 | 10 | | 44 | 8 | | 45 | 33 | | 46 | 2 | | 47 | 11 | | 48 | 24 | | 49 | 26 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 137 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 193 | | matches | (empty) | |
| 88.61% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 158 | | ratio | 0.019 | | matches | | 0 | "Then smell — crushed green stems and honey and wet earth in high summer, though September frost still silvered the grass outside." | | 1 | "Then movement between trunks — a flick of silver, gone." | | 2 | "Her lavender eyes flicked to Nyx, to the pillars behind, to the shimmer that hung between the trees where dusk pressed thin — a heat-haze distortion only visible when Rory squinted past Nyx's shoulder, there then gone." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1247 | | adjectiveStacks | 1 | | stackExamples | | 0 | "white against sudden gooseflesh." |
| | adverbCount | 39 | | adverbRatio | 0.03127506014434643 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0024057738572574178 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 158 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 158 | | mean | 9.11 | | std | 6.23 | | cv | 0.684 | | sampleLengths | | 0 | 13 | | 1 | 5 | | 2 | 18 | | 3 | 3 | | 4 | 7 | | 5 | 21 | | 6 | 6 | | 7 | 2 | | 8 | 16 | | 9 | 7 | | 10 | 5 | | 11 | 8 | | 12 | 7 | | 13 | 3 | | 14 | 6 | | 15 | 24 | | 16 | 3 | | 17 | 11 | | 18 | 10 | | 19 | 3 | | 20 | 3 | | 21 | 5 | | 22 | 22 | | 23 | 2 | | 24 | 3 | | 25 | 20 | | 26 | 10 | | 27 | 8 | | 28 | 5 | | 29 | 4 | | 30 | 19 | | 31 | 12 | | 32 | 1 | | 33 | 6 | | 34 | 14 | | 35 | 13 | | 36 | 13 | | 37 | 6 | | 38 | 4 | | 39 | 9 | | 40 | 10 | | 41 | 19 | | 42 | 15 | | 43 | 13 | | 44 | 2 | | 45 | 3 | | 46 | 4 | | 47 | 9 | | 48 | 10 | | 49 | 7 |
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| 62.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3987341772151899 | | totalSentences | 158 | | uniqueOpeners | 63 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 128 | | matches | | 0 | "Then smell — crushed green" | | 1 | "Then they gathered themselves, denser," | | 2 | "Further in, sound thickened." | | 3 | "Then movement between trunks —" |
| | ratio | 0.031 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 128 | | matches | | 0 | "It swallowed the path and" | | 1 | "Her breath fogged." | | 2 | "Her black hair stuck to" | | 3 | "She tugged her sleeve down" | | 4 | "Their edges smoked." | | 5 | "Their voice brushed past her" | | 6 | "It caught on Rory's lashes." | | 7 | "It dusted her coat." | | 8 | "They bloomed thick, stem over" | | 9 | "Her knee cracked." | | 10 | "She touched a poppy." | | 11 | "Their feet left no dent" | | 12 | "Her boot slipped." | | 13 | "She caught herself, palm flat" | | 14 | "She wiped her palm on" | | 15 | "Her breath sounded too loud." | | 16 | "She fished it out and" | | 17 | "Her phone showed 18:42 when" | | 18 | "It showed 18:41 now." | | 19 | "She stared at the numbers" |
| | ratio | 0.273 | |
| 34.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 109 | | totalSentences | 128 | | matches | | 0 | "The last dog walker left" | | 1 | "Mist pooled round her ankles." | | 2 | "It swallowed the path and" | | 3 | "Her breath fogged." | | 4 | "Her black hair stuck to" | | 5 | "She tugged her sleeve down" | | 6 | "Oak turned to stone, bark" | | 7 | "Lichen split the grain in" | | 8 | "Rory pressed her palm to" | | 9 | "Violet light kindled at her" | | 10 | "Nyx unfolded from the dark" | | 11 | "Their edges smoked." | | 12 | "Their voice brushed past her" | | 13 | "Rory stepped through." | | 14 | "The mist tore." | | 15 | "Dusk fell away." | | 16 | "A low gold noon filtered" | | 17 | "Trunks rose and rose and" | | 18 | "Pollen hung in the air" | | 19 | "It caught on Rory's lashes." |
| | ratio | 0.852 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 128 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 3 | | matches | | 0 | "Buttercups and poppies and things with no English name, white stars with blue throats, bells that rang without wind." | | 1 | "Her lavender eyes flicked to Nyx, to the pillars behind, to the shimmer that hung between the trees where dusk pressed thin — a heat-haze distortion only visibl…" | | 2 | "She glanced at Nyx, whose violet gaze fixed on the moonsilver with a hunger that hollowed their edges." |
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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 | |