| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 88.04% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1254 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "very" | | 1 | "eagerly" | | 2 | "completely" |
| |
| 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) | |
| 4.31% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1254 | | totalAiIsms | 24 | | found | | | highlights | | 0 | "etched" | | 1 | "familiar" | | 2 | "weight" | | 3 | "scanned" | | 4 | "warmth" | | 5 | "pulsed" | | 6 | "perfect" | | 7 | "silence" | | 8 | "flicker" | | 9 | "footsteps" | | 10 | "vibrated" | | 11 | "quivered" | | 12 | "quickened" | | 13 | "resolving" | | 14 | "chill" | | 15 | "synchronized" | | 16 | "mechanical" |
| |
| 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 | 1 | | narrationSentences | 123 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 123 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 129 | | 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 | 1254 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 1207 | | uniqueNames | 10 | | maxNameDensity | 0.25 | | worstName | "Aurora" | | maxWindowNameDensity | 1 | | worstWindowName | "London" | | discoveredNames | | Heartstone | 1 | | Pendant | 1 | | Richmond | 1 | | Park | 1 | | Golden | 1 | | Empress | 1 | | Cardiff | 2 | | London | 2 | | Silas | 1 | | Aurora | 3 |
| | persons | | 0 | "Pendant" | | 1 | "Silas" | | 2 | "Aurora" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Cardiff" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed taller now, their tops lost in the canopy" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1254 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 129 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 46.44 | | std | 24 | | cv | 0.517 | | sampleLengths | | 0 | 98 | | 1 | 91 | | 2 | 54 | | 3 | 26 | | 4 | 41 | | 5 | 68 | | 6 | 65 | | 7 | 13 | | 8 | 54 | | 9 | 82 | | 10 | 45 | | 11 | 43 | | 12 | 43 | | 13 | 73 | | 14 | 55 | | 15 | 9 | | 16 | 60 | | 17 | 49 | | 18 | 32 | | 19 | 12 | | 20 | 43 | | 21 | 41 | | 22 | 27 | | 23 | 52 | | 24 | 58 | | 25 | 18 | | 26 | 2 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 123 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 214 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 129 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1211 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 48 | | adverbRatio | 0.03963666391412056 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.008257638315441783 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 129 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 129 | | mean | 9.72 | | std | 6.38 | | cv | 0.657 | | sampleLengths | | 0 | 13 | | 1 | 24 | | 2 | 24 | | 3 | 37 | | 4 | 10 | | 5 | 28 | | 6 | 3 | | 7 | 22 | | 8 | 28 | | 9 | 9 | | 10 | 8 | | 11 | 9 | | 12 | 6 | | 13 | 14 | | 14 | 8 | | 15 | 15 | | 16 | 7 | | 17 | 4 | | 18 | 9 | | 19 | 5 | | 20 | 14 | | 21 | 2 | | 22 | 11 | | 23 | 5 | | 24 | 7 | | 25 | 12 | | 26 | 21 | | 27 | 8 | | 28 | 15 | | 29 | 4 | | 30 | 23 | | 31 | 2 | | 32 | 16 | | 33 | 2 | | 34 | 4 | | 35 | 14 | | 36 | 5 | | 37 | 8 | | 38 | 3 | | 39 | 22 | | 40 | 7 | | 41 | 10 | | 42 | 12 | | 43 | 4 | | 44 | 10 | | 45 | 12 | | 46 | 3 | | 47 | 17 | | 48 | 12 | | 49 | 10 |
| |
| 51.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.34108527131782945 | | totalSentences | 129 | | uniqueOpeners | 44 | |
| 86.21% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 116 | | matches | | 0 | "Too soft, as if the" | | 1 | "Instead the scrape gained companions," | | 2 | "Only the wildflowers remained, their" |
| | ratio | 0.026 | |
| 85.52% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 116 | | matches | | 0 | "She rubbed the crescent scar" | | 1 | "She had come because the" | | 2 | "Its crimson core had flared" | | 3 | "Her bright blue eyes scanned" | | 4 | "She rolled her shoulders once" | | 5 | "She crossed to the nearest" | | 6 | "Her voice fell flat, swallowed" | | 7 | "She pulled her hand away." | | 8 | "She moved toward the center." | | 9 | "Her black hair swung forward" | | 10 | "Its inner light spilled across" | | 11 | "She kept her face neutral." | | 12 | "She pivoted toward the closest" | | 13 | "Her mouth went dry." | | 14 | "She swallowed once and continued" | | 15 | "She had dismissed those tales" | | 16 | "She strode forward and rounded" | | 17 | "She was not alone." | | 18 | "She spoke again to keep" | | 19 | "They paced her from beyond" |
| | ratio | 0.336 | |
| 28.97% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 100 | | totalSentences | 116 | | matches | | 0 | "Aurora pushed through the last" | | 1 | "The ancient oak standing stones" | | 2 | "She rubbed the crescent scar" | | 3 | "The Heartstone Pendant rested against" | | 4 | "She had come because the" | | 5 | "Its crimson core had flared" | | 6 | "Answers waited here." | | 7 | "The unknown benefactor who left" | | 8 | "Her bright blue eyes scanned" | | 9 | "The ground felt wrong the" | | 10 | "She rolled her shoulders once" | | 11 | "The isolation dropped over her" | | 12 | "She crossed to the nearest" | | 13 | "Warmth pulsed back, synced to" | | 14 | "Her voice fell flat, swallowed" | | 15 | "She pulled her hand away." | | 16 | "A rustle answered from behind" | | 17 | "The flowers stood motionless, their" | | 18 | "She moved toward the center." | | 19 | "Each step pressed silence from" |
| | ratio | 0.862 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 116 | | matches | (empty) | | ratio | 0 | |
| 50.26% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 7 | | matches | | 0 | "The ancient oak standing stones rose in a ragged circle, their surfaces etched with spirals that caught the fragments of moonlight and held them." | | 1 | "The Heartstone Pendant rested against her collarbone, its silver chain cool at first, then warming in steady beats that matched the rhythm she had followed from…" | | 2 | "A fall from a garden wall in Cardiff that taught her consequences arrived without warning." | | 3 | "Eva’s urgent call that provided the escape route to London." | | 4 | "The part-time deliveries that paid just enough to keep her above Silas’s bar." | | 5 | "Shapes peeled away from the stones and hovered at the limits of her sight, tall and narrow, necks craned at angles that pinched her own shoulders in sympathy." | | 6 | "She spoke once more, cool-headed, buying time while her mind sorted escape vectors that kept shrinking." |
| |
| 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 | |