| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.01% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1671 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 46.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1671 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "flickered" | | 1 | "weight" | | 2 | "footsteps" | | 3 | "echoed" | | 4 | "reminder" | | 5 | "traced" | | 6 | "etched" | | 7 | "shattered" | | 8 | "sanctuary" | | 9 | "unspoken" | | 10 | "echo" | | 11 | "silence" | | 12 | "coded" | | 13 | "facade" | | 14 | "measured" |
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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 | 165 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 165 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 165 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1671 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 72 | | wordCount | 1669 | | uniqueNames | 16 | | maxNameDensity | 1.08 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | London | 1 | | Aurora | 18 | | Soho | 1 | | Empress | 1 | | Silas | 8 | | Prague | 2 | | Evan | 3 | | Cardiff | 2 | | Eva | 18 | | Spymaster | 2 | | Rory | 2 | | Carter | 1 | | Morse | 1 | | You | 10 |
| | persons | | 0 | "Raven" | | 1 | "Aurora" | | 2 | "Silas" | | 3 | "Evan" | | 4 | "Eva" | | 5 | "Spymaster" | | 6 | "Rory" | | 7 | "Carter" | | 8 | "You" |
| | places | | 0 | "London" | | 1 | "Prague" | | 2 | "Cardiff" |
| | globalScore | 0.961 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 109 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed tighter under the scrutiny, as if even her appearance fought to maintain the facade" |
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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 | 1671 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 165 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 41.78 | | std | 28.42 | | cv | 0.68 | | sampleLengths | | 0 | 110 | | 1 | 64 | | 2 | 1 | | 3 | 8 | | 4 | 7 | | 5 | 56 | | 6 | 15 | | 7 | 9 | | 8 | 47 | | 9 | 35 | | 10 | 10 | | 11 | 35 | | 12 | 54 | | 13 | 89 | | 14 | 34 | | 15 | 11 | | 16 | 44 | | 17 | 88 | | 18 | 4 | | 19 | 12 | | 20 | 62 | | 21 | 46 | | 22 | 54 | | 23 | 25 | | 24 | 60 | | 25 | 99 | | 26 | 8 | | 27 | 36 | | 28 | 59 | | 29 | 76 | | 30 | 43 | | 31 | 59 | | 32 | 48 | | 33 | 50 | | 34 | 43 | | 35 | 18 | | 36 | 32 | | 37 | 4 | | 38 | 90 | | 39 | 26 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 165 | | matches | | 0 | "tucked" | | 1 | "were supposed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 299 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 165 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1186 | | adjectiveStacks | 1 | | stackExamples | | 0 | "steady under grey-streaked brows." |
| | adverbCount | 41 | | adverbRatio | 0.03456998313659359 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.002529510961214165 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 165 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 165 | | mean | 10.13 | | std | 7.08 | | cv | 0.699 | | sampleLengths | | 0 | 18 | | 1 | 15 | | 2 | 16 | | 3 | 17 | | 4 | 12 | | 5 | 15 | | 6 | 17 | | 7 | 6 | | 8 | 7 | | 9 | 2 | | 10 | 13 | | 11 | 23 | | 12 | 13 | | 13 | 1 | | 14 | 5 | | 15 | 3 | | 16 | 1 | | 17 | 6 | | 18 | 5 | | 19 | 28 | | 20 | 13 | | 21 | 10 | | 22 | 15 | | 23 | 4 | | 24 | 5 | | 25 | 5 | | 26 | 17 | | 27 | 14 | | 28 | 8 | | 29 | 2 | | 30 | 1 | | 31 | 3 | | 32 | 15 | | 33 | 17 | | 34 | 4 | | 35 | 4 | | 36 | 2 | | 37 | 10 | | 38 | 25 | | 39 | 10 | | 40 | 3 | | 41 | 9 | | 42 | 6 | | 43 | 13 | | 44 | 13 | | 45 | 10 | | 46 | 11 | | 47 | 17 | | 48 | 16 | | 49 | 35 |
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| 63.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4 | | totalSentences | 165 | | uniqueOpeners | 66 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 149 | | matches | | 0 | "Then I heard you landed" | | 1 | "Suddenly deadlines mattered more than" | | 2 | "Instead you pedal through traffic" | | 3 | "Maybe you would have finished" | | 4 | "Maybe I wouldn’t have buried" |
| | ratio | 0.034 | |
| 93.83% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 47 | | totalSentences | 149 | | matches | | 0 | "She claimed her usual stool" | | 1 | "His neatly trimmed beard caught" | | 2 | "She dropped into the chair" | | 3 | "His silver signet ring tapped" | | 4 | "You look like money took" | | 5 | "I asked around before I" | | 6 | "Her straight black hair fell" | | 7 | "You hunted me down." | | 8 | "Her gaze drifted to the" | | 9 | "You never wrote." | | 10 | "I thought Evan found you" | | 11 | "You used to paint murals" | | 12 | "She grew up." | | 13 | "I close deals now." | | 14 | "She took a drink this" | | 15 | "They had been inseparable once." | | 16 | "I should have called." | | 17 | "We both rewrote our lines." | | 18 | "You were supposed to take" | | 19 | "He kept his distance but" |
| | ratio | 0.315 | |
| 77.45% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 114 | | totalSentences | 149 | | matches | | 0 | "Aurora pushed through the heavy" | | 1 | "Maps clung to the walls" | | 2 | "The green neon glow from" | | 3 | "She claimed her usual stool" | | 4 | "Silas slid a glass her" | | 5 | "His neatly trimmed beard caught" | | 6 | "The door creaked again behind" | | 7 | "Footsteps clicked across the floorboards" | | 8 | "A woman stood just inside," | | 9 | "Hair that used to tumble" | | 10 | "The face beneath it carried" | | 11 | "Aurora set her glass down." | | 12 | "The thud echoed." | | 13 | "Eva crossed the remaining distance." | | 14 | "She dropped into the chair" | | 15 | "Silas limped over, deposited two" | | 16 | "His silver signet ring tapped" | | 17 | "You look like money took" | | 18 | "Eva lifted one shoulder." | | 19 | "The suit whispered against itself." |
| | ratio | 0.765 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 149 | | matches | | 0 | "Now you're tucked above a" | | 1 | "Because I got tired of" | | 2 | "If I’d stayed longer, helped" | | 3 | "Now we sit here like" |
| | ratio | 0.027 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 76 | | technicalSentenceCount | 4 | | matches | | 0 | "The Aurora from Cardiff days once argued cases in mock court with a fire that cleared rooms." | | 1 | "This version sat in a bar that smelled of secrets and old ale, her quick mind now bent toward routes through back alleys and the weight of packages that sometim…" | | 2 | "My dad with his courtroom voice that followed us home like a shadow." | | 3 | "The guarded dullness cracked for a breath, revealing the friend who had driven through the night with a black eye already forming on Aurora’s face and fury in t…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |