| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 40 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1229 | | 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) | |
| 87.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1229 | | totalAiIsms | 3 | | found | | | highlights | | |
| 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 | 80 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 80 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1236 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 844 | | uniqueNames | 9 | | maxNameDensity | 0.83 | | worstName | "Whitaker" | | maxWindowNameDensity | 2 | | worstWindowName | "Whitaker" | | discoveredNames | | Tube | 1 | | Quinn | 4 | | Victorian | 1 | | Transport | 1 | | London | 1 | | Whitaker | 7 | | Morris | 1 | | Fleet | 1 | | August | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Victorian" | | 2 | "Whitaker" | | 3 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a compass rose every eight fe" |
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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 | 1236 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 32.53 | | std | 23.97 | | cv | 0.737 | | sampleLengths | | 0 | 55 | | 1 | 34 | | 2 | 3 | | 3 | 26 | | 4 | 58 | | 5 | 65 | | 6 | 28 | | 7 | 64 | | 8 | 52 | | 9 | 54 | | 10 | 60 | | 11 | 53 | | 12 | 6 | | 13 | 6 | | 14 | 47 | | 15 | 74 | | 16 | 24 | | 17 | 1 | | 18 | 1 | | 19 | 55 | | 20 | 18 | | 21 | 18 | | 22 | 66 | | 23 | 54 | | 24 | 27 | | 25 | 11 | | 26 | 6 | | 27 | 41 | | 28 | 5 | | 29 | 2 | | 30 | 4 | | 31 | 77 | | 32 | 40 | | 33 | 32 | | 34 | 19 | | 35 | 3 | | 36 | 4 | | 37 | 43 |
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| 92.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 80 | | matches | | 0 | "been dragged" | | 1 | "been opened" | | 2 | "been turned" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 146 | | matches | (empty) | |
| 37.04% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 108 | | ratio | 0.037 | | matches | | 0 | "The tape across the tiled archway read POLICE — DO NOT CROSS." | | 1 | "The tiles here carried a pattern — deep green and bone white — that she had not seen on any Transport for London heritage tour." | | 2 | "\"One of theirs.\" Whitaker tilted his head toward a group of figures held back near the stairwell — a dozen or more, wrapped in coats and scarves, watching." | | 3 | "Her eyes had adjusted; the tilework spirals continued the whole length of the platform, spirals and faces and something that looked like a compass rose every eight feet." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 738 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.014905149051490514 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 11.44 | | std | 8.2 | | cv | 0.716 | | sampleLengths | | 0 | 12 | | 1 | 12 | | 2 | 17 | | 3 | 14 | | 4 | 22 | | 5 | 12 | | 6 | 3 | | 7 | 17 | | 8 | 9 | | 9 | 11 | | 10 | 25 | | 11 | 1 | | 12 | 14 | | 13 | 7 | | 14 | 6 | | 15 | 29 | | 16 | 16 | | 17 | 14 | | 18 | 13 | | 19 | 13 | | 20 | 2 | | 21 | 10 | | 22 | 18 | | 23 | 8 | | 24 | 14 | | 25 | 5 | | 26 | 6 | | 27 | 3 | | 28 | 28 | | 29 | 21 | | 30 | 3 | | 31 | 2 | | 32 | 16 | | 33 | 8 | | 34 | 16 | | 35 | 12 | | 36 | 45 | | 37 | 15 | | 38 | 15 | | 39 | 11 | | 40 | 7 | | 41 | 2 | | 42 | 14 | | 43 | 4 | | 44 | 6 | | 45 | 6 | | 46 | 22 | | 47 | 25 | | 48 | 3 | | 49 | 10 |
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| 63.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.4444444444444444 | | totalSentences | 108 | | uniqueOpeners | 48 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 72.05% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 73 | | matches | | 0 | "She walked the platform edge," | | 1 | "She filed it away and" | | 2 | "She read it in the" | | 3 | "He had the look of" | | 4 | "She took in the scene" | | 5 | "She kept her knees off" | | 6 | "She looked at the coat" | | 7 | "She smelled her fingers without" | | 8 | "Her eyes had adjusted; the" | | 9 | "She walked to the nearest" | | 10 | "She looked back at the" | | 11 | "His shoes were polished." | | 12 | "She pointed at the scuffs" | | 13 | "He did not answer that." | | 14 | "He rubbed his jaw and" | | 15 | "He wanted a fence, a" | | 16 | "She knew the wanting." | | 17 | "She had wanted the same" | | 18 | "She moved along the platform" | | 19 | "She touched nothing." |
| | ratio | 0.37 | |
| 42.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 73 | | matches | | 0 | "The tape across the tiled" | | 1 | "Harlow Quinn ducked under the" | | 2 | "A constable held a lantern" | | 3 | "The constable pointed down the" | | 4 | "She walked the platform edge," | | 5 | "The tiles here carried a" | | 6 | "She filed it away and" | | 7 | "The station had been a" | | 8 | "She read it in the" | | 9 | "Booths of crates and draped" | | 10 | "Someone had tried to sweep" | | 11 | "DS Whitaker stood at the" | | 12 | "He had the look of" | | 13 | "She took in the scene" | | 14 | "The body lay between the" | | 15 | "A man, fifty-odd, in an" | | 16 | "Blood pooled beneath the head" | | 17 | "Whitaker tilted his head toward" | | 18 | "Whitaker closed his notebook" | | 19 | "She kept her knees off" |
| | ratio | 0.836 | |
| 68.49% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 73 | | matches | | 0 | "Whoever moved him held the" |
| | ratio | 0.014 | |
| 48.87% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 5 | | matches | | 0 | "Beyond it, the abandoned Tube platform opened into darkness that swallowed torchlight." | | 1 | "Harlow Quinn ducked under the tape and dropped onto the platform, her heels striking cracked Victorian tiling." | | 2 | "Her eyes had adjusted; the tilework spirals continued the whole length of the platform, spirals and faces and something that looked like a compass rose every ei…" | | 3 | "He wanted a fence, a robbery, a body that made sense in a report." | | 4 | "Small, heavy-looking, its face etched with sigils that matched the spirals on the tiles." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |