| 18.18% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 1 | | adverbTags | | 0 | "He stepped back [back]" |
| | dialogueSentences | 11 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0.333 | | effectiveRatio | 0.182 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1243 | | 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) | |
| 87.93% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1243 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "flickered" | | 1 | "silence" | | 2 | "velvet" |
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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 | 88 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 88 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 22 | | totalWords | 1243 | | ratio | 0.018 | | matches | | 0 | "Morris went into a dark place three years ago and something came back wearing his face for two days before anyone noticed." |
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| 75.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 1 | | matches | | 0 | "Evidence, she told herself." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1175 | | uniqueNames | 17 | | maxNameDensity | 0.6 | | worstName | "Herrera" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Herrera" | | discoveredNames | | Saint | 2 | | Christopher | 2 | | Tomás | 1 | | Herrera | 7 | | Raven | 1 | | Nest | 1 | | Camden | 1 | | High | 1 | | Street | 1 | | Lock | 1 | | Quinn | 6 | | Seville | 1 | | Tube | 1 | | Met | 1 | | Morris | 2 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Saint" | | 1 | "Christopher" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Raven" | | 5 | "Quinn" | | 6 | "Morris" | | 7 | "Market" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Lock" | | 4 | "Seville" |
| | globalScore | 1 | | windowScore | 1 | |
| 70.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 2 | | matches | | 0 | "something like it, flickered once at the bot" | | 1 | "something like grief crossed his face" |
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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 | 1243 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 31.87 | | std | 24.55 | | cv | 0.77 | | sampleLengths | | 0 | 14 | | 1 | 48 | | 2 | 2 | | 3 | 54 | | 4 | 71 | | 5 | 37 | | 6 | 57 | | 7 | 58 | | 8 | 52 | | 9 | 21 | | 10 | 15 | | 11 | 7 | | 12 | 8 | | 13 | 57 | | 14 | 7 | | 15 | 47 | | 16 | 56 | | 17 | 1 | | 18 | 44 | | 19 | 47 | | 20 | 9 | | 21 | 22 | | 22 | 101 | | 23 | 43 | | 24 | 22 | | 25 | 43 | | 26 | 61 | | 27 | 46 | | 28 | 11 | | 29 | 2 | | 30 | 6 | | 31 | 64 | | 32 | 17 | | 33 | 6 | | 34 | 2 | | 35 | 50 | | 36 | 20 | | 37 | 4 | | 38 | 11 |
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| 97.29% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 88 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 182 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 96 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1179 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.030534351145038167 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004240882103477523 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 12.95 | | std | 10.04 | | cv | 0.775 | | sampleLengths | | 0 | 14 | | 1 | 23 | | 2 | 20 | | 3 | 1 | | 4 | 1 | | 5 | 3 | | 6 | 2 | | 7 | 3 | | 8 | 32 | | 9 | 19 | | 10 | 24 | | 11 | 4 | | 12 | 13 | | 13 | 30 | | 14 | 2 | | 15 | 5 | | 16 | 21 | | 17 | 9 | | 18 | 31 | | 19 | 6 | | 20 | 2 | | 21 | 18 | | 22 | 17 | | 23 | 6 | | 24 | 35 | | 25 | 20 | | 26 | 11 | | 27 | 7 | | 28 | 14 | | 29 | 21 | | 30 | 1 | | 31 | 14 | | 32 | 7 | | 33 | 8 | | 34 | 6 | | 35 | 19 | | 36 | 12 | | 37 | 1 | | 38 | 19 | | 39 | 4 | | 40 | 3 | | 41 | 14 | | 42 | 19 | | 43 | 14 | | 44 | 4 | | 45 | 6 | | 46 | 46 | | 47 | 1 | | 48 | 15 | | 49 | 18 |
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| 71.88% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.5 | | totalSentences | 96 | | uniqueOpeners | 48 | |
| 86.58% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 77 | | matches | | 0 | "Then a voice, chewed up" | | 1 | "Then she looked at the" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 77 | | matches | | 0 | "He didn't stop." | | 1 | "He cut across Camden High" | | 2 | "He took the low tunnel" | | 3 | "She'd read the file twice." | | 4 | "He vaulted a construction hoarding" | | 5 | "Her hand closed around his" | | 6 | "he hissed, and wrenched free" | | 7 | "She heard it more than" | | 8 | "She looked down into the" | | 9 | "He held out a palm" | | 10 | "Her heartbeat counted out the" | | 11 | "She put Herrera's bone disc" | | 12 | "Her mind reached for the" | | 13 | "She checked her watch instead," | | 14 | "She pushed the thought down" | | 15 | "He had to be." | | 16 | "She found him at a" | | 17 | "His jacket was zipped against" | | 18 | "His hand hovered over a" | | 19 | "She kept her pace casual," |
| | ratio | 0.299 | |
| 89.87% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 77 | | matches | | 0 | "The Saint Christopher medallion caught" | | 1 | "Quinn was out of the" | | 2 | "He didn't stop." | | 3 | "He cut across Camden High" | | 4 | "Rain came down in sheets" | | 5 | "Herrera had the legs." | | 6 | "He took the low tunnel" | | 7 | "She'd read the file twice." | | 8 | "Knife wound, left forearm, Seville," | | 9 | "The file didn't say he" | | 10 | "He vaulted a construction hoarding" | | 11 | "Her hand closed around his" | | 12 | "Something snapped between them, small" | | 13 | "he hissed, and wrenched free" | | 14 | "Something fell from his jacket" | | 15 | "She heard it more than" | | 16 | "Quinn stood at the edge" | | 17 | "Herrera's torch beam, or something" | | 18 | "The radio gave up with" | | 19 | "She looked down into the" |
| | ratio | 0.74 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 77 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 1 | | matches | | 0 | "A door of black iron, seamless, set into the tunnel wall where no door had any right to be, and standing in front of it, filling most of the frame, was a shape …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 59.09% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 11 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0.5 | | effectiveRatio | 0.182 | |