| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 93 | | tagDensity | 0.151 | | leniency | 0.301 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.58% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2261 | | totalAiIsmAdverbs | 2 | | 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) | |
| 91.15% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2261 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "etched" | | 1 | "quivered" | | 2 | "unwavering" | | 3 | "comfortable" |
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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 | 200 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 200 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 276 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2256 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 27 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 65 | | wordCount | 1703 | | uniqueNames | 7 | | maxNameDensity | 1.7 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Sergeant | 1 | | Rook | 18 | | Quinn | 29 | | Vale | 8 | | Kowalski | 1 | | Eva | 7 |
| | persons | | 0 | "Sergeant" | | 1 | "Rook" | | 2 | "Quinn" | | 3 | "Vale" | | 4 | "Kowalski" | | 5 | "Eva" |
| | places | (empty) | | globalScore | 0.649 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 124 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed stronger than the stain warranted" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 0.887 | | wordCount | 2256 | | matches | | 0 | "not north, but toward the cabin’s back wall" | | 1 | "Not much, but enough to catch the light: a distinct skin of dark red acros" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 276 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 136 | | mean | 16.59 | | std | 17.76 | | cv | 1.071 | | sampleLengths | | 0 | 14 | | 1 | 76 | | 2 | 16 | | 3 | 55 | | 4 | 10 | | 5 | 48 | | 6 | 52 | | 7 | 21 | | 8 | 3 | | 9 | 10 | | 10 | 51 | | 11 | 3 | | 12 | 16 | | 13 | 3 | | 14 | 14 | | 15 | 5 | | 16 | 9 | | 17 | 10 | | 18 | 33 | | 19 | 44 | | 20 | 55 | | 21 | 6 | | 22 | 6 | | 23 | 1 | | 24 | 51 | | 25 | 10 | | 26 | 6 | | 27 | 5 | | 28 | 8 | | 29 | 4 | | 30 | 5 | | 31 | 42 | | 32 | 47 | | 33 | 6 | | 34 | 5 | | 35 | 4 | | 36 | 5 | | 37 | 1 | | 38 | 60 | | 39 | 3 | | 40 | 15 | | 41 | 5 | | 42 | 3 | | 43 | 5 | | 44 | 4 | | 45 | 5 | | 46 | 39 | | 47 | 5 | | 48 | 8 | | 49 | 1 |
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| 75.44% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 17 | | totalSentences | 200 | | matches | | 0 | "been closed" | | 1 | "been stripped" | | 2 | "been chained" | | 3 | "was built" | | 4 | "was covered" | | 5 | "was etched" | | 6 | "been logged" | | 7 | "was found" | | 8 | "was scuffed" | | 9 | "been disturbed" | | 10 | "been washed" | | 11 | "been questioned" | | 12 | "been carried" | | 13 | "been laid" | | 14 | "been lifted" | | 15 | "been placed" | | 16 | "been sealed" | | 17 | "been entered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 271 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 276 | | ratio | 0.014 | | matches | | 0 | "Beyond it, the abandoned Tube station lay crowded with the remnants of a market—folding tables, locked cases, a brass cage full of black feathers." | | 1 | "The market’s smells—wet stone, singed herbs, old pennies—seemed to press against her skin." | | 2 | "The chair back pressed against Vale’s shoulders; he would have had to be sitting quite still." | | 3 | "The false impression of a locked room, built around a body that had been carried—or brought—through a way none of them had seen." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1710 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 40 | | adverbRatio | 0.023391812865497075 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0023391812865497076 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 276 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 276 | | mean | 8.17 | | std | 5.67 | | cv | 0.694 | | sampleLengths | | 0 | 14 | | 1 | 30 | | 2 | 24 | | 3 | 8 | | 4 | 14 | | 5 | 7 | | 6 | 9 | | 7 | 12 | | 8 | 3 | | 9 | 14 | | 10 | 14 | | 11 | 8 | | 12 | 4 | | 13 | 10 | | 14 | 7 | | 15 | 3 | | 16 | 1 | | 17 | 13 | | 18 | 5 | | 19 | 19 | | 20 | 21 | | 21 | 10 | | 22 | 4 | | 23 | 4 | | 24 | 13 | | 25 | 5 | | 26 | 16 | | 27 | 3 | | 28 | 10 | | 29 | 5 | | 30 | 14 | | 31 | 8 | | 32 | 6 | | 33 | 18 | | 34 | 3 | | 35 | 16 | | 36 | 3 | | 37 | 14 | | 38 | 5 | | 39 | 5 | | 40 | 4 | | 41 | 5 | | 42 | 5 | | 43 | 6 | | 44 | 27 | | 45 | 21 | | 46 | 15 | | 47 | 8 | | 48 | 6 | | 49 | 16 |
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| 46.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.27898550724637683 | | totalSentences | 276 | | uniqueOpeners | 77 | |
| 56.18% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 178 | | matches | | 0 | "Too narrow for a person" | | 1 | "Then it snapped back toward" | | 2 | "Somewhere in that darkness, the" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 178 | | matches | | 0 | "He stepped aside." | | 1 | "She had taken it from" | | 2 | "She slipped it into her" | | 3 | "She kept her pace even." | | 4 | "His shirt was dark with" | | 5 | "It was a reasonable interpretation," | | 6 | "They made it easier to" | | 7 | "She crouched beside the cabin" | | 8 | "Its lower edge sat just" | | 9 | "She studied the chain." | | 10 | "She took a pair of" | | 11 | "He was perhaps sixty, with" | | 12 | "Its face was etched with" | | 13 | "It had been logged as" | | 14 | "She let the observation sit." | | 15 | "She moved around the chair." | | 16 | "She crouched, following the edge" | | 17 | "It sat on top of" | | 18 | "She looked at the knife" | | 19 | "She examined the floor near" |
| | ratio | 0.225 | |
| 41.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 149 | | totalSentences | 178 | | matches | | 0 | "The station had been closed" | | 1 | "Quinn saw it before she" | | 2 | "Quinn showed the bone token" | | 3 | "He stepped aside." | | 4 | "The token was no longer" | | 5 | "She had taken it from" | | 6 | "The man had claimed it" | | 7 | "Quinn had believed him." | | 8 | "She slipped it into her" | | 9 | "The air changed on the" | | 10 | "The market’s smells—wet stone, singed" | | 11 | "She kept her pace even." | | 12 | "Military precision, a colleague had" | | 13 | "The signalman’s cabin stood at" | | 14 | "A chain hung across the" | | 15 | "The padlock was intact." | | 16 | "Rook fell in beside her." | | 17 | "Quinn looked through the glass." | | 18 | "Vale sat in a wooden" | | 19 | "A narrow knife stood out" |
| | ratio | 0.837 | |
| 28.09% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 178 | | matches | | 0 | "Whoever had set the compass" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 68 | | technicalSentenceCount | 3 | | matches | | 0 | "It was a reasonable interpretation, offered with the confidence of a man who had already decided how much trouble he wanted." | | 1 | "A sharp, metallic tang that seemed stronger than the stain warranted." | | 2 | "Quinn recognized her from an interview two months earlier, when she had been questioned about a group of young people who kept turning up near scenes connected …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 93 | | tagDensity | 0.151 | | leniency | 0.301 | | rawRatio | 0 | | effectiveRatio | 0 | |