| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 55 | | tagDensity | 0.255 | | leniency | 0.509 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1610 | | 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) | |
| 25.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1610 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "pulse" | | 1 | "quickened" | | 2 | "jaw clenched" | | 3 | "echo" | | 4 | "weight" | | 5 | "pounding" | | 6 | "footsteps" | | 7 | "silence" | | 8 | "echoed" | | 9 | "traced" | | 10 | "tension" | | 11 | "shattered" | | 12 | "trembled" | | 13 | "warmth" | | 14 | "flickered" | | 15 | "vibrated" | | 16 | "pulsed" | | 17 | "unspoken" | | 18 | "whisper" | | 19 | "aftermath" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 206 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 206 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 246 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1600 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1320 | | uniqueNames | 12 | | maxNameDensity | 0.45 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Lucien | 6 | | Aurora | 6 | | Words | 1 | | Evan | 1 | | Eva | 1 | | Marseille | 1 | | Voice | 1 | | London | 1 | | Ptolemy | 5 | | Viaire | 1 | | Pages | 3 | | Ink | 4 |
| | persons | | 0 | "Lucien" | | 1 | "Aurora" | | 2 | "Words" | | 3 | "Evan" | | 4 | "Eva" | | 5 | "Voice" | | 6 | "Ptolemy" | | 7 | "Pages" | | 8 | "Ink" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 96.24% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 93 | | glossingSentenceCount | 2 | | matches | | 0 | "as if judging the intruder" | | 1 | "something like hope" |
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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 | 1600 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 246 | | matches | (empty) | |
| 93.73% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 102 | | mean | 15.69 | | std | 7.5 | | cv | 0.478 | | sampleLengths | | 0 | 13 | | 1 | 36 | | 2 | 16 | | 3 | 7 | | 4 | 28 | | 5 | 22 | | 6 | 14 | | 7 | 13 | | 8 | 5 | | 9 | 9 | | 10 | 33 | | 11 | 9 | | 12 | 14 | | 13 | 6 | | 14 | 14 | | 15 | 38 | | 16 | 16 | | 17 | 10 | | 18 | 17 | | 19 | 25 | | 20 | 7 | | 21 | 33 | | 22 | 20 | | 23 | 24 | | 24 | 9 | | 25 | 9 | | 26 | 8 | | 27 | 12 | | 28 | 9 | | 29 | 10 | | 30 | 24 | | 31 | 13 | | 32 | 26 | | 33 | 15 | | 34 | 21 | | 35 | 25 | | 36 | 19 | | 37 | 13 | | 38 | 19 | | 39 | 15 | | 40 | 8 | | 41 | 10 | | 42 | 8 | | 43 | 19 | | 44 | 15 | | 45 | 27 | | 46 | 16 | | 47 | 27 | | 48 | 13 | | 49 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 206 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 278 | | matches | | |
| 73.17% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 246 | | ratio | 0.024 | | matches | | 0 | "He just looked at her—one amber eye soft, the other black as midnight." | | 1 | "They both remembered the last time he’d asked for her help—only to vanish days later, leaving her with questions she’d spent sleepless nights trying to answer." | | 2 | "His scent—smoke and mint—sent a spark through her chest." | | 3 | "Lucien’s amber eye shone with triumph—and something softer, something she hadn’t expected." | | 4 | "Chest tight with adrenaline and something else—something like hope." | | 5 | "She looked into both his eyes—amber and black—and found the answer she hadn’t known she was seeking." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1328 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.02786144578313253 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0037650602409638554 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 246 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 246 | | mean | 6.5 | | std | 4.1 | | cv | 0.631 | | sampleLengths | | 0 | 5 | | 1 | 6 | | 2 | 2 | | 3 | 5 | | 4 | 11 | | 5 | 20 | | 6 | 4 | | 7 | 12 | | 8 | 4 | | 9 | 3 | | 10 | 3 | | 11 | 10 | | 12 | 15 | | 13 | 2 | | 14 | 7 | | 15 | 13 | | 16 | 6 | | 17 | 8 | | 18 | 6 | | 19 | 7 | | 20 | 3 | | 21 | 2 | | 22 | 7 | | 23 | 2 | | 24 | 12 | | 25 | 15 | | 26 | 2 | | 27 | 4 | | 28 | 9 | | 29 | 14 | | 30 | 3 | | 31 | 3 | | 32 | 10 | | 33 | 4 | | 34 | 5 | | 35 | 7 | | 36 | 26 | | 37 | 3 | | 38 | 11 | | 39 | 2 | | 40 | 3 | | 41 | 4 | | 42 | 3 | | 43 | 6 | | 44 | 7 | | 45 | 4 | | 46 | 6 | | 47 | 10 | | 48 | 9 | | 49 | 4 |
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| 47.97% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.2967479674796748 | | totalSentences | 246 | | uniqueOpeners | 73 | |
| 55.87% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 179 | | matches | | 0 | "Then back at her." | | 1 | "Then shadow claimed it." | | 2 | "Flat, powerful tones that vibrated" |
| | ratio | 0.017 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 103 | | totalSentences | 179 | | matches | | 0 | "His tailored charcoal suit cut" | | 1 | "She took a breath." | | 2 | "Her wrist brushed the crescent" | | 3 | "He stepped in." | | 4 | "She crossed her arms, scuffing" | | 5 | "He just looked at her—one" | | 6 | "She cut off" | | 7 | "His shoulders stiffened." | | 8 | "He set the cane by" | | 9 | "She stepped back, offering him" | | 10 | "Her refuge after Evan." | | 11 | "He glanced around, lips smoothing" | | 12 | "He tilted his head toward" | | 13 | "Her pulse quickened." | | 14 | "He inhaled, a tidy breath" | | 15 | "She glanced at the scar," | | 16 | "They both remembered the last" | | 17 | "She turned away." | | 18 | "His jaw clenched." | | 19 | "He refused to wince." |
| | ratio | 0.575 | |
| 18.66% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 158 | | totalSentences | 179 | | matches | | 0 | "Aurora eased the door open." | | 1 | "Lamplight spilled into the narrow" | | 2 | "Lucien waited on the threshold." | | 3 | "His tailored charcoal suit cut" | | 4 | "The ivory handle of his" | | 5 | "She took a breath." | | 6 | "Her wrist brushed the crescent" | | 7 | "The door swung wider." | | 8 | "He stepped in." | | 9 | "Rory’s cheeks tightened." | | 10 | "She crossed her arms, scuffing" | | 11 | "Ptolemy, the tabby from next" | | 12 | "He just looked at her—one" | | 13 | "She cut off" | | 14 | "Words packed too tight, rattling" | | 15 | "Rain tapped the window behind" | | 16 | "The city murmured beyond the" | | 17 | "His shoulders stiffened." | | 18 | "He set the cane by" | | 19 | "She stepped back, offering him" |
| | ratio | 0.883 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 179 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 2 | | matches | | 0 | "She sensed the gravity, the stakes that stretched beyond her door." | | 1 | "Her mind shot back to dimly lit nights, to his lips brushing hers, to the soft promises that shattered when he vanished in Marseille." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 95.45% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 3 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "he whispered (whisper)" | | 2 | "he breathed (breathe)" |
| | dialogueSentences | 55 | | tagDensity | 0.127 | | leniency | 0.255 | | rawRatio | 0.429 | | effectiveRatio | 0.109 | |