| 82.35% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 3 | | adverbTags | | 0 | "She brushed away [away]" | | 1 | "She hesitated then [then]" | | 2 | "He inhaled deeply [deeply]" |
| | dialogueSentences | 51 | | tagDensity | 0.314 | | leniency | 0.627 | | rawRatio | 0.188 | | effectiveRatio | 0.118 | |
| 78.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1151 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "sharply" | | 2 | "slowly" | | 3 | "cautiously" |
| |
| 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1151 | | totalAiIsms | 25 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | |
| | highlights | | 0 | "loomed" | | 1 | "echoed" | | 2 | "silence" | | 3 | "echoing" | | 4 | "chill" | | 5 | "etched" | | 6 | "flickered" | | 7 | "unreadable" | | 8 | "stomach" | | 9 | "scanning" | | 10 | "shattered" | | 11 | "velvet" | | 12 | "flicked" | | 13 | "tension" | | 14 | "perfect" | | 15 | "traced" | | 16 | "pulse" | | 17 | "quickened" | | 18 | "vibrated" | | 19 | "grave" | | 20 | "scanned" | | 21 | "pounding" | | 22 | "pulsed" |
| |
| 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 | 0 | | narrationSentences | 84 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 84 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | 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 | 1145 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 24.34% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 756 | | uniqueNames | 8 | | maxNameDensity | 2.51 | | worstName | "Harlow" | | maxWindowNameDensity | 4 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 19 | | Quinn | 1 | | Tube | 1 | | Veil | 1 | | Compass | 1 | | Eva | 10 | | Kowalski | 1 | | Graves | 10 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Compass" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Graves" |
| | places | (empty) | | globalScore | 0.243 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1145 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 118 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 27.93 | | std | 17.8 | | cv | 0.637 | | sampleLengths | | 0 | 88 | | 1 | 68 | | 2 | 45 | | 3 | 40 | | 4 | 47 | | 5 | 35 | | 6 | 38 | | 7 | 16 | | 8 | 38 | | 9 | 25 | | 10 | 34 | | 11 | 14 | | 12 | 35 | | 13 | 5 | | 14 | 39 | | 15 | 28 | | 16 | 6 | | 17 | 34 | | 18 | 26 | | 19 | 11 | | 20 | 14 | | 21 | 49 | | 22 | 12 | | 23 | 15 | | 24 | 8 | | 25 | 51 | | 26 | 8 | | 27 | 42 | | 28 | 8 | | 29 | 26 | | 30 | 20 | | 31 | 17 | | 32 | 40 | | 33 | 32 | | 34 | 7 | | 35 | 36 | | 36 | 18 | | 37 | 20 | | 38 | 10 | | 39 | 34 | | 40 | 6 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 84 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 151 | | matches | (empty) | |
| 46.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 118 | | ratio | 0.034 | | matches | | 0 | "She’d bought it from a vendor whose eyes had flickered with something unreadable—something that made her stomach twist." | | 1 | "The station’s center was littered with debris—broken timetables, shattered glass, and something darker smeared across the floor." | | 2 | "“Someone wanted us to find this.” She brushed away grime, revealing faint stitching that formed an unfamiliar sigil—a spiral intertwined with thorns." | | 3 | "Memories surged—her partner’s death, the unexplained energy readings, the way shadows seemed to move independently." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 572 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.033216783216783216 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.017482517482517484 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 9.7 | | std | 5.82 | | cv | 0.599 | | sampleLengths | | 0 | 20 | | 1 | 19 | | 2 | 18 | | 3 | 19 | | 4 | 12 | | 5 | 9 | | 6 | 3 | | 7 | 3 | | 8 | 16 | | 9 | 19 | | 10 | 18 | | 11 | 9 | | 12 | 18 | | 13 | 13 | | 14 | 5 | | 15 | 5 | | 16 | 17 | | 17 | 4 | | 18 | 4 | | 19 | 10 | | 20 | 16 | | 21 | 22 | | 22 | 9 | | 23 | 6 | | 24 | 22 | | 25 | 7 | | 26 | 3 | | 27 | 21 | | 28 | 14 | | 29 | 10 | | 30 | 6 | | 31 | 17 | | 32 | 11 | | 33 | 10 | | 34 | 11 | | 35 | 14 | | 36 | 8 | | 37 | 26 | | 38 | 4 | | 39 | 10 | | 40 | 4 | | 41 | 19 | | 42 | 12 | | 43 | 2 | | 44 | 3 | | 45 | 24 | | 46 | 15 | | 47 | 7 | | 48 | 13 | | 49 | 8 |
| |
| 76.84% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.4661016949152542 | | totalSentences | 118 | | uniqueOpeners | 55 | |
| 85.47% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 78 | | matches | | 0 | "Too viscous, too deliberate." | | 1 | "Somewhere in the distance, a" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 78 | | matches | | 0 | "Her leather watch glinted dully" | | 1 | "She moved forward, boots echoing" | | 2 | "Its brass casing felt warm" | | 3 | "She’d bought it from a" | | 4 | "She carried a battered satchel" | | 5 | "she asked, voice low but" | | 6 | "She held it up, revealing" | | 7 | "She brushed away grime, revealing" | | 8 | "She glanced toward the tunnel" | | 9 | "Her gaze flicked to Harlow," | | 10 | "They turned to see a" | | 11 | "His posture radiated authority, though" | | 12 | "He gestured toward the far" | | 13 | "She hesitated, then met" | | 14 | "He glanced at Harlow" | | 15 | "Her breath hitched." | | 16 | "She pointed to a series" | | 17 | "He pointed to a section" | | 18 | "He inhaled deeply, then recoiled" | | 19 | "He glanced at Harlow" |
| | ratio | 0.282 | |
| 24.10% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 78 | | matches | | 0 | "Detective Harlow Quinn stepped off" | | 1 | "The air hung thick with" | | 2 | "Her leather watch glinted dully" | | 3 | "The platform loomed like a" | | 4 | "A faint metallic scent drifted" | | 5 | "Harlow’s jaw tightened." | | 6 | "Something wasn’t right." | | 7 | "She moved forward, boots echoing" | | 8 | "Its brass casing felt warm" | | 9 | "She’d bought it from a" | | 10 | "Eva Kowalski emerged, her curly" | | 11 | "She carried a battered satchel" | | 12 | "Harlow nodded, scanning the space." | | 13 | "The station’s center was littered" | | 14 | "she asked, voice low but" | | 15 | "Eva knelt beside a smear," | | 16 | "She held it up, revealing" | | 17 | "Harlow crouched beside her, eyes" | | 18 | "She brushed away grime, revealing" | | 19 | "Eva exhaled sharply." |
| | ratio | 0.872 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 78 | | matches | | 0 | "Now, silence pressed in, broken" | | 1 | "Before Harlow could respond, a" |
| | ratio | 0.026 | |
| 68.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 3 | | matches | | 0 | "Detective Harlow Quinn stepped off the rickety tram that had deposited her at the edge of the abandoned Tube station." | | 1 | "Its brass casing felt warm despite the chill, the protective sigils etched into its surface catching the dim light." | | 2 | "She’d bought it from a vendor whose eyes had flickered with something unreadable—something that made her stomach twist." |
| |
| 93.75% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 1 | | matches | | 0 | "she asked, voice low but steady" |
| |
| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 3 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "she murmured (murmur)" | | 2 | "he muttered (mutter)" |
| | dialogueSentences | 51 | | tagDensity | 0.078 | | leniency | 0.157 | | rawRatio | 0.75 | | effectiveRatio | 0.118 | |