| 30.51% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 27 | | adverbTagCount | 5 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "she said suddenly [suddenly]" | | 2 | "Quinn said quietly [quietly]" | | 3 | "they said softly [softly]" | | 4 | "Quinn said quietly [quietly]" |
| | dialogueSentences | 59 | | tagDensity | 0.458 | | leniency | 0.915 | | rawRatio | 0.185 | | effectiveRatio | 0.169 | |
| 83.50% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1212 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "suddenly" | | 2 | "softly" |
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| 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) | |
| 17.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1212 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "perfect" | | 1 | "glinting" | | 2 | "etched" | | 3 | "traced" | | 4 | "scanning" | | 5 | "echoing" | | 6 | "silence" | | 7 | "footsteps" | | 8 | "echoed" | | 9 | "gleaming" | | 10 | "pulse" | | 11 | "quickened" | | 12 | "pounding" | | 13 | "determined" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 125 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 125 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 157 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1210 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 66 | | wordCount | 872 | | uniqueNames | 6 | | maxNameDensity | 4.47 | | worstName | "Quinn" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 39 | | Davies | 23 | | Tube | 1 | | Footsteps | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Davies" | | 3 | "Footsteps" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like an inverted triangle with a c" |
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| 34.71% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.653 | | wordCount | 1210 | | matches | | 0 | "Not the usual grime of the underground, but something sharper, metallic" | | 1 | "not just blood now, but something acrid, like burnt hair" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 157 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 82 | | mean | 14.76 | | std | 10.82 | | cv | 0.733 | | sampleLengths | | 0 | 25 | | 1 | 44 | | 2 | 42 | | 3 | 17 | | 4 | 37 | | 5 | 6 | | 6 | 24 | | 7 | 12 | | 8 | 28 | | 9 | 4 | | 10 | 20 | | 11 | 47 | | 12 | 8 | | 13 | 20 | | 14 | 5 | | 15 | 36 | | 16 | 36 | | 17 | 7 | | 18 | 10 | | 19 | 47 | | 20 | 3 | | 21 | 16 | | 22 | 8 | | 23 | 34 | | 24 | 6 | | 25 | 4 | | 26 | 16 | | 27 | 20 | | 28 | 6 | | 29 | 19 | | 30 | 3 | | 31 | 11 | | 32 | 8 | | 33 | 14 | | 34 | 24 | | 35 | 8 | | 36 | 23 | | 37 | 11 | | 38 | 8 | | 39 | 22 | | 40 | 5 | | 41 | 12 | | 42 | 5 | | 43 | 8 | | 44 | 19 | | 45 | 11 | | 46 | 22 | | 47 | 6 | | 48 | 3 | | 49 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 125 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 182 | | matches | (empty) | |
| 70.06% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 157 | | ratio | 0.025 | | matches | | 0 | "Graffiti covered most of the space––names, dates, crude drawings." | | 1 | "The smell grew stronger as they walked––not just blood now, but something acrid, like burnt hair." | | 2 | "The flashlight beam caught something ahead––a faint glow, like a lantern." | | 3 | "They disappeared into the shadows as Quinn lunged forward, her boots pounding against the tracks––but they were already gone." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 873 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small leather-bound notebook." |
| | adverbCount | 31 | | adverbRatio | 0.035509736540664374 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.01718213058419244 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 157 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 157 | | mean | 7.71 | | std | 5.11 | | cv | 0.663 | | sampleLengths | | 0 | 12 | | 1 | 11 | | 2 | 1 | | 3 | 1 | | 4 | 12 | | 5 | 22 | | 6 | 10 | | 7 | 9 | | 8 | 15 | | 9 | 9 | | 10 | 1 | | 11 | 8 | | 12 | 6 | | 13 | 11 | | 14 | 3 | | 15 | 13 | | 16 | 5 | | 17 | 16 | | 18 | 2 | | 19 | 4 | | 20 | 8 | | 21 | 16 | | 22 | 6 | | 23 | 6 | | 24 | 7 | | 25 | 17 | | 26 | 4 | | 27 | 4 | | 28 | 2 | | 29 | 18 | | 30 | 12 | | 31 | 15 | | 32 | 10 | | 33 | 10 | | 34 | 8 | | 35 | 3 | | 36 | 13 | | 37 | 4 | | 38 | 5 | | 39 | 2 | | 40 | 34 | | 41 | 3 | | 42 | 7 | | 43 | 26 | | 44 | 4 | | 45 | 3 | | 46 | 6 | | 47 | 4 | | 48 | 12 | | 49 | 9 |
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| 66.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.40764331210191085 | | totalSentences | 157 | | uniqueOpeners | 64 | |
| 33.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 99 | | matches | | 0 | "Then, faintly, the sound of" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 99 | | matches | | 0 | "He stood near the edge" | | 1 | "Her clothes were neat, but" | | 2 | "She pulled a pair of" | | 3 | "Her movements were precise, military." | | 4 | "She pointed to the rusted" | | 5 | "She stepped closer, her flashlight" | | 6 | "She picked it up, turning" | | 7 | "Her fingers traced the verdigris" | | 8 | "It didn’t point north." | | 9 | "she said quietly" | | 10 | "She slipped the compass into" | | 11 | "She stepped away from the" | | 12 | "It looked like an inverted" | | 13 | "He joined her, his flashlight" | | 14 | "She took a photo with" | | 15 | "Her flashlight beam lingered on" | | 16 | "She turned, scanning the platform" | | 17 | "she said suddenly" | | 18 | "He rifled through the woman’s" | | 19 | "She approached the alcove, her" |
| | ratio | 0.263 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 95 | | totalSentences | 99 | | matches | | 0 | "The stench hit Detective Harlow" | | 1 | "He stood near the edge" | | 2 | "Quinn crouched beside the body," | | 3 | "The woman lay sprawled on" | | 4 | "Her clothes were neat, but" | | 5 | "Quinn tilted her head, taking" | | 6 | "Quinn’s eyes narrowed." | | 7 | "She pulled a pair of" | | 8 | "Her movements were precise, military." | | 9 | "She pointed to the rusted" | | 10 | "Quinn said, leaning closer" | | 11 | "Davies hesitated, then crouched beside" | | 12 | "Quinn straightened, her gaze sweeping" | | 13 | "The abandoned station was eerily" | | 14 | "Something she couldn’t place." | | 15 | "Quinn’s eyes caught on something" | | 16 | "She stepped closer, her flashlight" | | 17 | "She picked it up, turning" | | 18 | "The casing was weathered, etched" | | 19 | "Davies said, glancing at the" |
| | ratio | 0.96 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 99 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 13.89% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 27 | | uselessAdditionCount | 6 | | matches | | 0 | "Quinn said, her voice low" | | 1 | "Davies asked, his voice echoing" | | 2 | "Davies said, his voice trembling slightly" | | 3 | "Quinn called, her voice firm" | | 4 | "Davies echoed, his voice uncertain" | | 5 | "Quinn said quietly, her voice low" |
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| 48.31% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 23 | | fancyCount | 6 | | fancyTags | | 0 | "Davies continued (continue)" | | 1 | "she murmured (murmur)" | | 2 | "Davies whispered (whisper)" | | 3 | "Davies muttered (mutter)" | | 4 | "Quinn barked (bark)" | | 5 | "he muttered (mutter)" |
| | dialogueSentences | 59 | | tagDensity | 0.39 | | leniency | 0.78 | | rawRatio | 0.261 | | effectiveRatio | 0.203 | |