| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "he shouted back [back]" |
| | dialogueSentences | 24 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.125 | | effectiveRatio | 0.083 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1684 | | 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) | |
| 82.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1684 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "flickered" | | 3 | "etched" | | 4 | "flicked" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 152 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 152 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 167 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1684 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 1420 | | uniqueNames | 18 | | maxNameDensity | 0.99 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 14 | | Raven | 1 | | Nest | 1 | | Camden | 6 | | Morris | 3 | | Underground | 1 | | Tube | 3 | | Veil | 1 | | Market | 1 | | One | 2 | | London | 1 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Seville | 1 | | Tomás | 4 | | Fear | 3 | | Eighteen | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Camden" | | 2 | "Morris" | | 3 | "Market" | | 4 | "One" | | 5 | "Herrera" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Tomás" | | 9 | "Fear" |
| | places | | 0 | "Raven" | | 1 | "London" | | 2 | "Seville" |
| | globalScore | 1 | | windowScore | 1 | |
| 98.98% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 98 | | glossingSentenceCount | 2 | | matches | | 0 | "as if guarding something" | | 1 | "not quite some tall and too thin, some with eyes that reflected the torchlight wrong" |
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| 81.24% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.188 | | wordCount | 1684 | | matches | | 0 | "not the white glare of Tube fluorescents but a warm amber wash" | | 1 | "No law down here but" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 167 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 70 | | mean | 24.06 | | std | 19.14 | | cv | 0.796 | | sampleLengths | | 0 | 10 | | 1 | 41 | | 2 | 3 | | 3 | 22 | | 4 | 83 | | 5 | 7 | | 6 | 8 | | 7 | 9 | | 8 | 21 | | 9 | 81 | | 10 | 5 | | 11 | 12 | | 12 | 17 | | 13 | 30 | | 14 | 9 | | 15 | 13 | | 16 | 55 | | 17 | 66 | | 18 | 48 | | 19 | 14 | | 20 | 43 | | 21 | 22 | | 22 | 10 | | 23 | 54 | | 24 | 9 | | 25 | 11 | | 26 | 32 | | 27 | 9 | | 28 | 56 | | 29 | 9 | | 30 | 73 | | 31 | 18 | | 32 | 26 | | 33 | 9 | | 34 | 34 | | 35 | 11 | | 36 | 16 | | 37 | 16 | | 38 | 7 | | 39 | 19 | | 40 | 19 | | 41 | 19 | | 42 | 9 | | 43 | 9 | | 44 | 11 | | 45 | 35 | | 46 | 7 | | 47 | 47 | | 48 | 21 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 152 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 242 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 167 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1420 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.027464788732394368 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0035211267605633804 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 167 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 167 | | mean | 10.08 | | std | 7.83 | | cv | 0.776 | | sampleLengths | | 0 | 10 | | 1 | 16 | | 2 | 12 | | 3 | 13 | | 4 | 3 | | 5 | 4 | | 6 | 18 | | 7 | 2 | | 8 | 17 | | 9 | 15 | | 10 | 33 | | 11 | 8 | | 12 | 3 | | 13 | 5 | | 14 | 7 | | 15 | 8 | | 16 | 9 | | 17 | 3 | | 18 | 3 | | 19 | 1 | | 20 | 4 | | 21 | 10 | | 22 | 9 | | 23 | 3 | | 24 | 17 | | 25 | 6 | | 26 | 14 | | 27 | 7 | | 28 | 9 | | 29 | 1 | | 30 | 15 | | 31 | 3 | | 32 | 2 | | 33 | 3 | | 34 | 5 | | 35 | 4 | | 36 | 17 | | 37 | 30 | | 38 | 9 | | 39 | 13 | | 40 | 3 | | 41 | 2 | | 42 | 13 | | 43 | 26 | | 44 | 11 | | 45 | 11 | | 46 | 13 | | 47 | 15 | | 48 | 12 | | 49 | 3 |
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| 52.61% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.37349397590361444 | | totalSentences | 166 | | uniqueOpeners | 62 | |
| 24.88% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 134 | | matches | | 0 | "Pale, hollow cheeked, a smear" |
| | ratio | 0.007 | |
| 88.66% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 44 | | totalSentences | 134 | | matches | | 0 | "He slipped on the kerb" | | 1 | "His trainers squeaked on the" | | 2 | "He did not stop." | | 3 | "He vaulted a low wall" | | 4 | "Her boots hit the wet" | | 5 | "She caught the edge of" | | 6 | "He knew better." | | 7 | "He kept to the alley." | | 8 | "She gained on him by" | | 9 | "he shouted back without turning" | | 10 | "His voice cracked." | | 11 | "She checked her left wrist" | | 12 | "She had chased him for" | | 13 | "He turned north." | | 14 | "He was not running blind." | | 15 | "He had a destination." | | 16 | "She radioed with one hand" | | 17 | "She clicked off." | | 18 | "She did not hold position" | | 19 | "He glanced back again." |
| | ratio | 0.328 | |
| 38.36% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 113 | | totalSentences | 134 | | matches | | 0 | "He slipped on the kerb" | | 1 | "The boy, no older than" | | 2 | "His trainers squeaked on the" | | 3 | "Quinn lost half a second" | | 4 | "He did not stop." | | 5 | "He vaulted a low wall" | | 6 | "Her boots hit the wet" | | 7 | "The distinctive green neon sign" | | 8 | "She caught the edge of" | | 9 | "The boy did not head" | | 10 | "He knew better." | | 11 | "He kept to the alley." | | 12 | "She gained on him by" | | 13 | "he shouted back without turning" | | 14 | "His voice cracked." | | 15 | "Fear made people stupid." | | 16 | "The alley spat them out" | | 17 | "Traffic hissed past." | | 18 | "A bus sent a sheet" | | 19 | "Copper stung her nostrils from" |
| | ratio | 0.843 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 134 | | matches | (empty) | | ratio | 0 | |
| 68.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 6 | | matches | | 0 | "Pale, hollow cheeked, a smear of something dark at the corner of his mouth that was not dirt." | | 1 | "The kind of air that had clung to Morris's coat when they found him." | | 2 | "Light second, not the white glare of Tube fluorescents but a warm amber wash that flickered like candlelight though no candles burned." | | 3 | "People crowded the edges, not people, not quite, some tall and too thin, some with eyes that reflected the torchlight wrong." | | 4 | "He knocked over a crate of bottles as he ran and the bottles smashed and released a plume of violet smoke that curled into faces and made them cough." | | 5 | "From the side tunnel the boy had aimed for, something answered the flare, a wet click clack that echoed too loud, too jointed, as if many legs moved on tile." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 66.67% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 2 | | fancyTags | | 0 | "he shouted back (shout)" | | 1 | "he breathed (breathe)" |
| | dialogueSentences | 24 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.25 | | effectiveRatio | 0.167 | |