| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 58 | | tagDensity | 0.138 | | leniency | 0.276 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 99.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 5833 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 94.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 5833 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "silence" | | 1 | "scanned" | | 2 | "gloom" | | 3 | "pulsed" | | 4 | "footsteps" |
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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 | 1417 | | matches | (empty) | |
| 92.45% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 50 | | hedgeCount | 0 | | narrationSentences | 1417 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 1467 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 5833 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 307 | | wordCount | 5606 | | uniqueNames | 8 | | maxNameDensity | 3.01 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Quinn" | | discoveredNames | | Kensington | 1 | | High | 1 | | Street | 1 | | Harlow | 11 | | Quinn | 169 | | St | 1 | | Tomás | 122 | | Hallow | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" |
| | places | | 0 | "Kensington" | | 1 | "High" | | 2 | "Street" | | 3 | "St" | | 4 | "Hallow" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 5833 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 1467 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 1358 | | mean | 4.3 | | std | 4.01 | | cv | 0.933 | | sampleLengths | | 0 | 50 | | 1 | 43 | | 2 | 2 | | 3 | 18 | | 4 | 2 | | 5 | 47 | | 6 | 4 | | 7 | 11 | | 8 | 3 | | 9 | 36 | | 10 | 3 | | 11 | 26 | | 12 | 60 | | 13 | 20 | | 14 | 8 | | 15 | 30 | | 16 | 43 | | 17 | 19 | | 18 | 5 | | 19 | 15 | | 20 | 12 | | 21 | 5 | | 22 | 32 | | 23 | 5 | | 24 | 18 | | 25 | 36 | | 26 | 16 | | 27 | 7 | | 28 | 6 | | 29 | 5 | | 30 | 11 | | 31 | 35 | | 32 | 3 | | 33 | 3 | | 34 | 16 | | 35 | 6 | | 36 | 14 | | 37 | 13 | | 38 | 13 | | 39 | 7 | | 40 | 6 | | 41 | 10 | | 42 | 6 | | 43 | 25 | | 44 | 21 | | 45 | 4 | | 46 | 4 | | 47 | 15 | | 48 | 18 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 9 | | totalSentences | 1417 | | matches | | 0 | "was obscured" | | 1 | "was wrapped" | | 2 | "was made" | | 3 | "was gone" | | 4 | "was gone" | | 5 | "was gone" | | 6 | "was gone" | | 7 | "was gone" | | 8 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 1453 | | matches | | 0 | "were going" | | 1 | "was cleaning" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 1467 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 5610 | | adjectiveStacks | 1 | | stackExamples | | 0 | "damp pressed against her" |
| | adverbCount | 29 | | adverbRatio | 0.00516934046345811 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.00017825311942959 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 1467 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 1467 | | mean | 3.98 | | std | 1.83 | | cv | 0.461 | | sampleLengths | | 0 | 20 | | 1 | 16 | | 2 | 14 | | 3 | 22 | | 4 | 3 | | 5 | 3 | | 6 | 15 | | 7 | 2 | | 8 | 3 | | 9 | 15 | | 10 | 2 | | 11 | 4 | | 12 | 8 | | 13 | 14 | | 14 | 21 | | 15 | 4 | | 16 | 4 | | 17 | 7 | | 18 | 3 | | 19 | 4 | | 20 | 19 | | 21 | 5 | | 22 | 8 | | 23 | 3 | | 24 | 5 | | 25 | 5 | | 26 | 6 | | 27 | 8 | | 28 | 2 | | 29 | 10 | | 30 | 16 | | 31 | 9 | | 32 | 8 | | 33 | 5 | | 34 | 12 | | 35 | 4 | | 36 | 2 | | 37 | 2 | | 38 | 12 | | 39 | 8 | | 40 | 4 | | 41 | 6 | | 42 | 5 | | 43 | 10 | | 44 | 5 | | 45 | 5 | | 46 | 8 | | 47 | 2 | | 48 | 6 | | 49 | 10 |
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| 25.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 548 | | diversityRatio | 0.03749147920927062 | | totalSentences | 1467 | | uniqueOpeners | 55 | |
| 8.68% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 1152 | | matches | | 0 | "Just the pipes running overhead" | | 1 | "Then the tunnels." | | 2 | "Then the unknown." |
| | ratio | 0.003 | |
| 94.31% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 362 | | totalSentences | 1152 | | matches | | 0 | "Her salt-and-pepper hair clung to" | | 1 | "She didn't shout." | | 2 | "She hated the noise, but" | | 3 | "His face was obscured by" | | 4 | "He sidestepped into a gap" | | 5 | "He pulled a thick wire" | | 6 | "She descended the ladder she’d" | | 7 | "Her boot found a rung," | | 8 | "Her red wrist plate clicked" | | 9 | "She looked at her watch." | | 10 | "She moved toward the noise." | | 11 | "Her military bearing kept her" | | 12 | "She crested a concrete mound." | | 13 | "He held a small medallion" | | 14 | "His scarred left forearm was" | | 15 | "He looked worse than she" | | 16 | "He didn't see her at" | | 17 | "He was cleaning a needle" | | 18 | "He looked up." | | 19 | "Her flat palms thumped against" |
| | ratio | 0.314 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 1143 | | totalSentences | 1152 | | matches | | 0 | "Detective Harlow Quinn kept her" | | 1 | "Her salt-and-pepper hair clung to" | | 2 | "The figure moved away from" | | 3 | "Quinn didn't shout." | | 4 | "She didn't shout." | | 5 | "She hated the noise, but" | | 6 | "The man turned." | | 7 | "His face was obscured by" | | 8 | "The man didn't react." | | 9 | "He sidestepped into a gap" | | 10 | "Quinn slid past him, boots" | | 11 | "The man slipped toward a" | | 12 | "Harlow pulled her handgun." | | 13 | "The cold steel hummed against" | | 14 | "The man ignored her." | | 15 | "He pulled a thick wire" | | 16 | "Sparks flew behind the grating." | | 17 | "The metal groaned and lifted" | | 18 | "The alley swallowed the man." | | 19 | "The air grew thick, unfiltered." |
| | ratio | 0.992 | |
| 4.34% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 1152 | | matches | | 0 | "Before the man could speak," |
| | ratio | 0.001 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 3 | | matches | | 0 | "The figure moved away from the curb, draped in a heavy plastic bag that slumped over his shoulders like a second hide." | | 1 | "Quinn slid past him, boots splashing in a puddle that reflected her brown eyes." | | 2 | "Her military bearing kept her torso stiff, shoulders rolling forward." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 58 | | tagDensity | 0.086 | | leniency | 0.172 | | rawRatio | 0 | | effectiveRatio | 0 | |