| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.517 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1580 | | 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) | |
| 71.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1580 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "churned" | | 1 | "eyebrow" | | 2 | "stomach" | | 3 | "etched" | | 4 | "flickered" | | 5 | "unwavering" | | 6 | "restrained" | | 7 | "traced" | | 8 | "rhythmic" |
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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 | 104 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 104 | | filterMatches | | | hedgeMatches | (empty) | |
| 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 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1569 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1186 | | uniqueNames | 9 | | maxNameDensity | 0.93 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Webb" | | discoveredNames | | Tube | 1 | | Harlow | 2 | | Quinn | 11 | | Camden | 1 | | Victorian | 1 | | Sergeant | 1 | | Nathan | 1 | | Webb | 10 | | Morris | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Nathan" | | 4 | "Webb" | | 5 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.637 | | wordCount | 1569 | | matches | | 0 | "not with magnetism but with something else, a silent urgency" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 118 | | matches | | 0 | "buried that file" | | 1 | "find that woman" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 46.15 | | std | 31.55 | | cv | 0.684 | | sampleLengths | | 0 | 115 | | 1 | 65 | | 2 | 38 | | 3 | 82 | | 4 | 37 | | 5 | 81 | | 6 | 6 | | 7 | 69 | | 8 | 85 | | 9 | 18 | | 10 | 42 | | 11 | 3 | | 12 | 69 | | 13 | 34 | | 14 | 12 | | 15 | 52 | | 16 | 27 | | 17 | 93 | | 18 | 3 | | 19 | 10 | | 20 | 41 | | 21 | 14 | | 22 | 38 | | 23 | 71 | | 24 | 6 | | 25 | 23 | | 26 | 64 | | 27 | 30 | | 28 | 14 | | 29 | 63 | | 30 | 13 | | 31 | 57 | | 32 | 99 | | 33 | 95 |
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| 85.02% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 104 | | matches | | 0 | "been arranged" | | 1 | "were unlaced" | | 2 | "been dragged" | | 3 | "was clenched" | | 4 | "been sealed" | | 5 | "been placed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 198 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 118 | | ratio | 0.059 | | matches | | 0 | "The stale air in the abandoned Tube tunnel tasted of old soot and something sharper—dried herbs, maybe, or ozone." | | 1 | "The floor told the same story—no smears, no disturbance in the powdery grime." | | 2 | "His left was clenched around something—a small brass object, the patina a sickly green of verdigris." | | 3 | "She traced the outline with a gloved finger—a box, maybe, or a book." | | 4 | "A marker, maybe—or a key." | | 5 | "She felt it then—a pressure in her ears, a low thrum at the edge of hearing, like a train rumbling miles away." | | 6 | "The woman who’d called it in knew the location—knew it well enough to bypass the locked grate and leave no trace." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1197 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.02506265664160401 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.005847953216374269 | |
| 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 | 13.3 | | std | 8.93 | | cv | 0.672 | | sampleLengths | | 0 | 19 | | 1 | 24 | | 2 | 31 | | 3 | 18 | | 4 | 23 | | 5 | 10 | | 6 | 16 | | 7 | 19 | | 8 | 10 | | 9 | 10 | | 10 | 12 | | 11 | 19 | | 12 | 7 | | 13 | 29 | | 14 | 17 | | 15 | 18 | | 16 | 2 | | 17 | 8 | | 18 | 8 | | 19 | 4 | | 20 | 25 | | 21 | 8 | | 22 | 3 | | 23 | 12 | | 24 | 12 | | 25 | 9 | | 26 | 10 | | 27 | 10 | | 28 | 12 | | 29 | 13 | | 30 | 6 | | 31 | 51 | | 32 | 18 | | 33 | 2 | | 34 | 8 | | 35 | 16 | | 36 | 6 | | 37 | 21 | | 38 | 1 | | 39 | 2 | | 40 | 29 | | 41 | 10 | | 42 | 8 | | 43 | 12 | | 44 | 3 | | 45 | 18 | | 46 | 9 | | 47 | 3 | | 48 | 3 | | 49 | 8 |
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| 58.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3983050847457627 | | totalSentences | 118 | | uniqueOpeners | 47 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 94 | | matches | (empty) | | ratio | 0 | |
| 83.83% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 94 | | matches | | 0 | "Her left wrist ached from" | | 1 | "She counted eighteen years on" | | 2 | "She swallowed the thought and" | | 3 | "He was thirty-two, a year" | | 4 | "She stopped at the edge" | | 5 | "His coat, a long leather" | | 6 | "He gestured at the empty" | | 7 | "She pulled on a pair" | | 8 | "His shoes were unlaced, the" | | 9 | "She noted the absence of" | | 10 | "His left was clenched around" | | 11 | "She gently pried the fingers" | | 12 | "It swung in a lazy" | | 13 | "She shifted her position and" | | 14 | "She lifted the compass closer" | | 15 | "she said, not looking away" | | 16 | "She stood and pointed at" | | 17 | "She traced the outline with" | | 18 | "She picked it up." | | 19 | "She turned the token over" |
| | ratio | 0.34 | |
| 18.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 94 | | matches | | 0 | "The stale air in the" | | 1 | "Detective Harlow Quinn swept her" | | 2 | "The stairs from the Camden" | | 3 | "A generator-powered floodlight threw harsh" | | 4 | "Quinn ducked under a sagging" | | 5 | "Her left wrist ached from" | | 6 | "She counted eighteen years on" | | 7 | "Morris would have made a" | | 8 | "She swallowed the thought and" | | 9 | "Detective Sergeant Nathan Webb straightened" | | 10 | "He was thirty-two, a year" | | 11 | "She stopped at the edge" | | 12 | "A man lay on his" | | 13 | "His coat, a long leather" | | 14 | "The concrete beneath him was" | | 15 | "Webb followed her gaze." | | 16 | "He gestured at the empty" | | 17 | "Quinn didn’t answer." | | 18 | "She pulled on a pair" | | 19 | "The man’s skin held a" |
| | ratio | 0.883 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 94 | | matches | | 0 | "If he’d dragged himself or" | | 1 | "To send a message." |
| | ratio | 0.021 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 4 | | matches | | 0 | "Detective Harlow Quinn swept her torch across the platform, the beam cutting through a haze of dust motes that churned like a living thing." | | 1 | "A man lay on his back, arms at his sides, legs straight as if he’d been arranged." | | 2 | "A professional hit in a hidden market, but the killer had taken nothing and left a compass that functioned like no instrument she’d ever seen." | | 3 | "She would find that woman, and she would find out what lay behind a wall that shouldn’t breathe and shouldn’t beat." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 3 | | matches | | 0 | "She stopped, her eyes moving across the scene" | | 1 | "she said, not looking away from the archway" | | 2 | "She turned, her voice flat" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 29 | | tagDensity | 0.207 | | leniency | 0.414 | | rawRatio | 0.167 | | effectiveRatio | 0.069 | |