| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 87.03% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1542 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "sharply" | | 1 | "carefully" | | 2 | "quickly" | | 3 | "slowly" |
| |
| 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) | |
| 57.85% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1542 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "chill" | | 1 | "effortless" | | 2 | "uncanny" | | 3 | "firmly" | | 4 | "weight" | | 5 | "pulse" | | 6 | "throbbed" | | 7 | "echo" | | 8 | "silence" | | 9 | "flickered" | | 10 | "measured" | | 11 | "traced" | | 12 | "fractured" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 172 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 172 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 172 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1542 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 6 | | matches | | 0 | "You locked three deadbolts, he murmured, voice rolling through the syllables with a Marseille cadence that always made t…" | | 1 | "I never apologized because I knew you would not accept it, he said." | | 2 | "You walked out, she said quietly." | | 3 | "You look different, she murmured." | | 4 | "I care, she whispered." | | 5 | "Then say it again, he said." |
| |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1542 | | uniqueNames | 17 | | maxNameDensity | 0.65 | | worstName | "You" | | maxWindowNameDensity | 2 | | worstWindowName | "You" | | discoveredNames | | November | 1 | | East | 1 | | London | 2 | | Moreau | 1 | | Marseille | 1 | | Tuesday | 1 | | Evan | 1 | | Luc | 2 | | Yu-Fei | 2 | | Cheung | 1 | | Empress | 1 | | Silas | 1 | | Aur | 1 | | Wales | 1 | | Docklands | 1 | | Aurora | 4 | | You | 10 |
| | persons | | 0 | "Moreau" | | 1 | "Evan" | | 2 | "Luc" | | 3 | "Yu-Fei" | | 4 | "Cheung" | | 5 | "Silas" | | 6 | "Aurora" | | 7 | "You" |
| | places | | 0 | "East" | | 1 | "London" | | 2 | "Marseille" | | 3 | "Empress" | | 4 | "Wales" | | 5 | "Docklands" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 112 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed smaller with him in it, the air thicker" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1542 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 172 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 33.52 | | std | 28.33 | | cv | 0.845 | | sampleLengths | | 0 | 89 | | 1 | 81 | | 2 | 28 | | 3 | 22 | | 4 | 35 | | 5 | 3 | | 6 | 2 | | 7 | 96 | | 8 | 61 | | 9 | 7 | | 10 | 69 | | 11 | 26 | | 12 | 45 | | 13 | 2 | | 14 | 2 | | 15 | 60 | | 16 | 51 | | 17 | 27 | | 18 | 5 | | 19 | 40 | | 20 | 5 | | 21 | 3 | | 22 | 10 | | 23 | 42 | | 24 | 73 | | 25 | 22 | | 26 | 53 | | 27 | 3 | | 28 | 51 | | 29 | 9 | | 30 | 15 | | 31 | 80 | | 32 | 5 | | 33 | 21 | | 34 | 2 | | 35 | 36 | | 36 | 12 | | 37 | 4 | | 38 | 67 | | 39 | 43 | | 40 | 10 | | 41 | 69 | | 42 | 89 | | 43 | 16 | | 44 | 35 | | 45 | 16 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 172 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 296 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 172 | | ratio | 0.006 | | matches | | 0 | "The black eye darkened; the amber one caught the overhead bulb." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1548 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 60 | | adverbRatio | 0.03875968992248062 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.009689922480620155 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 172 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 172 | | mean | 8.97 | | std | 6.32 | | cv | 0.704 | | sampleLengths | | 0 | 9 | | 1 | 30 | | 2 | 15 | | 3 | 21 | | 4 | 14 | | 5 | 5 | | 6 | 23 | | 7 | 24 | | 8 | 8 | | 9 | 21 | | 10 | 26 | | 11 | 2 | | 12 | 15 | | 13 | 5 | | 14 | 2 | | 15 | 13 | | 16 | 3 | | 17 | 7 | | 18 | 6 | | 19 | 6 | | 20 | 3 | | 21 | 2 | | 22 | 8 | | 23 | 33 | | 24 | 23 | | 25 | 17 | | 26 | 4 | | 27 | 11 | | 28 | 10 | | 29 | 12 | | 30 | 21 | | 31 | 11 | | 32 | 7 | | 33 | 7 | | 34 | 7 | | 35 | 16 | | 36 | 4 | | 37 | 19 | | 38 | 13 | | 39 | 10 | | 40 | 4 | | 41 | 9 | | 42 | 13 | | 43 | 6 | | 44 | 9 | | 45 | 12 | | 46 | 8 | | 47 | 10 | | 48 | 2 | | 49 | 2 |
| |
| 76.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4883720930232558 | | totalSentences | 172 | | uniqueOpeners | 84 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 156 | | matches | | 0 | "Bright blue eyes narrowed as" | | 1 | "Still waking up clutching your" | | 2 | "Especially when it involves half-breeds" | | 3 | "Then I will use the" | | 4 | "Just an empty coat rack" | | 5 | "Still costing favors." | | 6 | "Somewhere below, a siren wailed," | | 7 | "Then say it again, he" |
| | ratio | 0.051 | |
| 61.03% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 62 | | totalSentences | 156 | | matches | | 0 | "He filled the cramped frame" | | 1 | "He carried the scent of" | | 2 | "You locked three deadbolts, he" | | 3 | "I lock them every night." | | 4 | "He stepped forward." | | 5 | "She planted her feet, spine" | | 6 | "His shadow swallowed the dim" | | 7 | "She remembered the taste of" | | 8 | "She remembered telling him he" | | 9 | "He had not argued." | | 10 | "He had simply adjusted his" | | 11 | "You are tracking mud on" | | 12 | "Your floor has been stained" | | 13 | "He set the ivory cane" | | 14 | "She watched the motion, trained" | | 15 | "She crossed her arms, elbows" | | 16 | "His gaze dropped to her" | | 17 | "You signed up for Yu-Fei" | | 18 | "She turned away, pacing toward" | | 19 | "Her boots squeaked on linoleum." |
| | ratio | 0.397 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 109 | | totalSentences | 156 | | matches | | 0 | "The brass bolt scraped back" | | 1 | "Aurora stood in the threshold," | | 2 | "Lucien Moreau did not blink." | | 3 | "He filled the cramped frame" | | 4 | "The weak fluorescent tube caught" | | 5 | "Ivory cane planted firmly on" | | 6 | "He carried the scent of" | | 7 | "You locked three deadbolts, he" | | 8 | "Aurora shifted her weight, the" | | 9 | "I lock them every night." | | 10 | "He stepped forward." | | 11 | "She planted her feet, spine" | | 12 | "His shadow swallowed the dim" | | 13 | "The admission hung between them," | | 14 | "She remembered the taste of" | | 15 | "She remembered telling him he" | | 16 | "He had not argued." | | 17 | "He had simply adjusted his" | | 18 | "Ptolemy slipped around her ankles," | | 19 | "The tabby mewed once, a" |
| | ratio | 0.699 | |
| 64.10% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 156 | | matches | | 0 | "If you are here to" | | 1 | "If you are here to" |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 65 | | technicalSentenceCount | 2 | | matches | | 0 | "Something flickered there, regret, maybe, or exhaustion, or the same stubborn pull that had kept them tangled in rooftops and safe houses while the city's under…" | | 1 | "She turned it on, letting it run over her wrists, feeling the heat bleed into old scars." |
| |
| 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 | |