| 26.09% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 2 | | adverbTags | | 0 | "Brennan rocked back [back]" | | 1 | "Eva's charcoal hovered then [then]" |
| | dialogueSentences | 23 | | tagDensity | 0.304 | | leniency | 0.609 | | rawRatio | 0.286 | | effectiveRatio | 0.174 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1389 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 78.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1389 | | totalAiIsms | 6 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "the last thing" | | count | 1 |
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| | highlights | | 0 | "trembled" | | 1 | "silk" | | 2 | "measured" | | 3 | "etched" | | 4 | "the last thing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1389 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 1016 | | uniqueNames | 14 | | maxNameDensity | 0.79 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Brennan" | | discoveredNames | | Veil | 1 | | Market | 3 | | Brennan | 6 | | Kowalski | 1 | | Shade | 1 | | Kess | 2 | | Eva | 6 | | Quinn | 8 | | Transport | 1 | | London | 1 | | Morris | 2 | | Tube | 1 | | Camden | 1 | | Met | 1 |
| | persons | | 0 | "Market" | | 1 | "Brennan" | | 2 | "Kowalski" | | 3 | "Eva" | | 4 | "Quinn" | | 5 | "Morris" | | 6 | "Met" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 1 | | matches | | 0 | "smelled like this one, myrrh and copper, a" |
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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 | 1389 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 124 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 28.94 | | std | 20.12 | | cv | 0.695 | | sampleLengths | | 0 | 10 | | 1 | 21 | | 2 | 40 | | 3 | 18 | | 4 | 23 | | 5 | 4 | | 6 | 4 | | 7 | 7 | | 8 | 48 | | 9 | 34 | | 10 | 53 | | 11 | 39 | | 12 | 2 | | 13 | 54 | | 14 | 38 | | 15 | 62 | | 16 | 4 | | 17 | 59 | | 18 | 46 | | 19 | 47 | | 20 | 30 | | 21 | 19 | | 22 | 58 | | 23 | 8 | | 24 | 6 | | 25 | 56 | | 26 | 10 | | 27 | 30 | | 28 | 64 | | 29 | 22 | | 30 | 26 | | 31 | 4 | | 32 | 57 | | 33 | 18 | | 34 | 68 | | 35 | 35 | | 36 | 49 | | 37 | 4 | | 38 | 14 | | 39 | 34 | | 40 | 43 | | 41 | 9 | | 42 | 49 | | 43 | 26 | | 44 | 10 | | 45 | 11 | | 46 | 13 | | 47 | 3 |
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| 95.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 108 | | matches | | 0 | "been snapped" | | 1 | "been required" | | 2 | "been heated" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 170 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 124 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1017 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.03146509341199607 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0019665683382497543 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 11.2 | | std | 9.47 | | cv | 0.846 | | sampleLengths | | 0 | 10 | | 1 | 6 | | 2 | 15 | | 3 | 17 | | 4 | 8 | | 5 | 13 | | 6 | 1 | | 7 | 1 | | 8 | 18 | | 9 | 23 | | 10 | 4 | | 11 | 4 | | 12 | 7 | | 13 | 6 | | 14 | 18 | | 15 | 4 | | 16 | 20 | | 17 | 8 | | 18 | 9 | | 19 | 5 | | 20 | 12 | | 21 | 20 | | 22 | 18 | | 23 | 15 | | 24 | 22 | | 25 | 17 | | 26 | 2 | | 27 | 54 | | 28 | 8 | | 29 | 25 | | 30 | 5 | | 31 | 12 | | 32 | 17 | | 33 | 2 | | 34 | 12 | | 35 | 14 | | 36 | 1 | | 37 | 4 | | 38 | 4 | | 39 | 13 | | 40 | 9 | | 41 | 5 | | 42 | 2 | | 43 | 6 | | 44 | 8 | | 45 | 8 | | 46 | 8 | | 47 | 5 | | 48 | 5 | | 49 | 13 |
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| 69.62% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.47580645161290325 | | totalSentences | 124 | | uniqueOpeners | 59 | |
| 72.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 92 | | matches | | 0 | "Dark purple had settled along" | | 1 | "Only the signature." |
| | ratio | 0.022 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 92 | | matches | | 0 | "He had died flat." | | 1 | "She checked her own wrist" | | 2 | "It told her nothing useful," | | 3 | "She tucked a curl of" | | 4 | "She adjusted her glasses" | | 5 | "She moved the way she" | | 6 | "She catalogued as she walked." | | 7 | "He had belonged here." | | 8 | "She lifted the right hand." | | 9 | "It did not point at" | | 10 | "It held, stubborn, on that" | | 11 | "She tucked hair behind her" | | 12 | "She scraped a flake of" | | 13 | "She thought of Morris without" | | 14 | "She had stopped telling people" | | 15 | "She kept her voice low," | | 16 | "She tucked hair behind her" | | 17 | "She pressed the heel of" |
| | ratio | 0.196 | |
| 19.78% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 81 | | totalSentences | 92 | | matches | | 0 | "Quinn peeled the brass compass" | | 1 | "The needle trembled, then locked" | | 2 | "The Veil Market sprawled across" | | 3 | "Copper lamps still burned along" | | 4 | "Myrrh hung in the air," | | 5 | "DS Brennan crouched on the" | | 6 | "Quinn shifted the man's left" | | 7 | "He had died flat." | | 8 | "Someone had sat him up," | | 9 | "She checked her own wrist" | | 10 | "The worn leather watch sat" | | 11 | "It told her nothing useful," | | 12 | "Eva Kowalski stood inside the" | | 13 | "She tucked a curl of" | | 14 | "Freckles stood out dark against" | | 15 | "She adjusted her glasses" | | 16 | "She moved the way she" | | 17 | "She catalogued as she walked." | | 18 | "The nearest stall still held" | | 19 | "A tray of bone tokens" |
| | ratio | 0.88 | |
| 54.35% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 92 | | matches | | 0 | "Whoever opened that box wanted" |
| | ratio | 0.011 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 4 | | matches | | 0 | "She moved the way she always moved at a scene, shoulders square, steps measured, the old military precision that made junior officers give her room." | | 1 | "The platform narrowed toward the old run-off, where the Market's back stalls gave way to bare tile and a brick bulkhead that had no business looking new." | | 2 | "A case that had ended in a room that smelled like this one, myrrh and copper, and a partner who had been there and then had not, the explanation filed under cir…" | | 3 | "She kept her voice low, academic habit, as if the bricks were a reading room." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.043 | | leniency | 0.087 | | rawRatio | 0 | | effectiveRatio | 0 | |