| 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 | 1507 | | 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) | |
| 53.55% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1507 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "pulse" | | 1 | "throb" | | 2 | "echo" | | 3 | "warmth" | | 4 | "pulsed" | | 5 | "stomach" | | 6 | "silence" | | 7 | "footsteps" | | 8 | "weight" |
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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 | 181 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 181 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 188 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1507 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1463 | | uniqueNames | 9 | | maxNameDensity | 0.89 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Park | 1 | | Carter | 1 | | Heartstone | 5 | | Fae | 1 | | Grove | 1 | | Roehampton | 1 | | Richmond | 2 | | Aurora | 13 | | Flowers | 3 |
| | persons | | 0 | "Carter" | | 1 | "Heartstone" | | 2 | "Aurora" | | 3 | "Flowers" |
| | places | | 0 | "Park" | | 1 | "Fae" | | 2 | "Grove" | | 3 | "Richmond" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 104 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.664 | | wordCount | 1507 | | matches | | 0 | "not as oak but as figures with bark for skin" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 188 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 29.55 | | std | 19.71 | | cv | 0.667 | | sampleLengths | | 0 | 9 | | 1 | 95 | | 2 | 10 | | 3 | 57 | | 4 | 32 | | 5 | 9 | | 6 | 28 | | 7 | 62 | | 8 | 22 | | 9 | 5 | | 10 | 31 | | 11 | 2 | | 12 | 29 | | 13 | 39 | | 14 | 7 | | 15 | 4 | | 16 | 67 | | 17 | 16 | | 18 | 26 | | 19 | 43 | | 20 | 20 | | 21 | 12 | | 22 | 12 | | 23 | 43 | | 24 | 74 | | 25 | 22 | | 26 | 28 | | 27 | 22 | | 28 | 39 | | 29 | 20 | | 30 | 2 | | 31 | 44 | | 32 | 46 | | 33 | 10 | | 34 | 39 | | 35 | 26 | | 36 | 44 | | 37 | 36 | | 38 | 11 | | 39 | 45 | | 40 | 24 | | 41 | 42 | | 42 | 29 | | 43 | 11 | | 44 | 54 | | 45 | 22 | | 46 | 41 | | 47 | 22 | | 48 | 4 | | 49 | 46 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 181 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 228 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 188 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1465 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.024573378839590442 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 188 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 188 | | mean | 8.02 | | std | 5.61 | | cv | 0.7 | | sampleLengths | | 0 | 5 | | 1 | 4 | | 2 | 14 | | 3 | 27 | | 4 | 10 | | 5 | 19 | | 6 | 8 | | 7 | 17 | | 8 | 10 | | 9 | 7 | | 10 | 17 | | 11 | 9 | | 12 | 3 | | 13 | 6 | | 14 | 3 | | 15 | 5 | | 16 | 7 | | 17 | 8 | | 18 | 16 | | 19 | 8 | | 20 | 9 | | 21 | 8 | | 22 | 2 | | 23 | 18 | | 24 | 6 | | 25 | 8 | | 26 | 5 | | 27 | 19 | | 28 | 3 | | 29 | 4 | | 30 | 6 | | 31 | 11 | | 32 | 4 | | 33 | 2 | | 34 | 10 | | 35 | 6 | | 36 | 5 | | 37 | 2 | | 38 | 7 | | 39 | 5 | | 40 | 6 | | 41 | 3 | | 42 | 4 | | 43 | 4 | | 44 | 2 | | 45 | 5 | | 46 | 9 | | 47 | 9 | | 48 | 6 | | 49 | 3 |
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| 50.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3351063829787234 | | totalSentences | 188 | | uniqueOpeners | 63 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 158 | | matches | | 0 | "Bright blue caught the pendant" | | 1 | "Then a scrape." | | 2 | "Then the hand withdrew." | | 3 | "Then the pendant pulsed once," | | 4 | "Then they showed as stones" |
| | ratio | 0.032 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 158 | | matches | | 0 | "Her bike leaned against the" | | 1 | "She pulled the silver chain" | | 2 | "She came because the stone" | | 3 | "Her breath made a cloud" | | 4 | "She passed between the first" | | 5 | "Her voice hit the arch" | | 6 | "She rubbed her left wrist" | | 7 | "She curled her fingers around" | | 8 | "She checked her phone." | | 9 | "She shoved it in her" | | 10 | "She took a step toward" | | 11 | "Her footprint stayed pressed flat," | | 12 | "She turned her head." | | 13 | "She moved to see around" | | 14 | "She circled the ring with" | | 15 | "Her straight black hair caught" | | 16 | "She pushed it behind her" | | 17 | "She whirled and threw a" | | 18 | "Her palm met cold." | | 19 | "She held the pose, chest" |
| | ratio | 0.253 | |
| 54.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 128 | | totalSentences | 158 | | matches | | 0 | "Richmond Park locked at dusk." | | 1 | "The gate stood open." | | 2 | "Aurora Carter stared at the" | | 3 | "Her bike leaned against the" | | 4 | "She pulled the silver chain" | | 5 | "The Heartstone pendant sat in" | | 6 | "Heat beat against her skin" | | 7 | "She came because the stone" | | 8 | "The Fae Grove lay beyond" | | 9 | "Wildflowers broke through frost-hard ground" | | 10 | "Aurora stepped off the path" | | 11 | "Sound fell away." | | 12 | "Traffic from Roehampton cut off" | | 13 | "Her breath made a cloud" | | 14 | "She passed between the first" | | 15 | "The trunks rose and twisted" | | 16 | "Her voice hit the arch" | | 17 | "She rubbed her left wrist" | | 18 | "The grove opened in a" | | 19 | "Grass grew thick and soft" |
| | ratio | 0.81 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 158 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 2 | | matches | | 0 | "Pressure brushed her neck, as if someone exhaled close to skin." | | 1 | "A line of stems bowed and sprang back, ten feet long, as if something low and long pushed through them and passed out of sight behind the next stone." |
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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 | |