| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 74 | | tagDensity | 0.176 | | leniency | 0.351 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1550 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 87.10% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1550 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "measured" | | 1 | "quivered" | | 2 | "standard" |
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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 | 137 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 137 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 198 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1550 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 80.37% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1149 | | uniqueNames | 5 | | maxNameDensity | 1.39 | | worstName | "Patel" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Patel" | | discoveredNames | | Quinn | 1 | | Camden | 1 | | Niall | 1 | | Patel | 16 | | Harlow | 15 |
| | persons | | 0 | "Quinn" | | 1 | "Niall" | | 2 | "Patel" | | 3 | "Harlow" |
| | places | (empty) | | globalScore | 0.804 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 95 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1550 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 198 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 110 | | mean | 14.09 | | std | 13.61 | | cv | 0.966 | | sampleLengths | | 0 | 4 | | 1 | 28 | | 2 | 8 | | 3 | 4 | | 4 | 3 | | 5 | 38 | | 6 | 8 | | 7 | 25 | | 8 | 55 | | 9 | 16 | | 10 | 46 | | 11 | 23 | | 12 | 14 | | 13 | 2 | | 14 | 26 | | 15 | 7 | | 16 | 10 | | 17 | 3 | | 18 | 11 | | 19 | 50 | | 20 | 3 | | 21 | 26 | | 22 | 2 | | 23 | 9 | | 24 | 1 | | 25 | 4 | | 26 | 9 | | 27 | 17 | | 28 | 12 | | 29 | 59 | | 30 | 6 | | 31 | 38 | | 32 | 12 | | 33 | 3 | | 34 | 4 | | 35 | 7 | | 36 | 48 | | 37 | 12 | | 38 | 9 | | 39 | 9 | | 40 | 38 | | 41 | 4 | | 42 | 2 | | 43 | 4 | | 44 | 3 | | 45 | 11 | | 46 | 38 | | 47 | 28 | | 48 | 7 | | 49 | 13 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 137 | | matches | | 0 | "been bolted" | | 1 | "been placed" |
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| 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 | 198 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1152 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.017361111111111112 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0026041666666666665 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 198 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 198 | | mean | 7.83 | | std | 4.6 | | cv | 0.587 | | sampleLengths | | 0 | 4 | | 1 | 13 | | 2 | 15 | | 3 | 4 | | 4 | 4 | | 5 | 4 | | 6 | 3 | | 7 | 4 | | 8 | 7 | | 9 | 15 | | 10 | 12 | | 11 | 5 | | 12 | 3 | | 13 | 7 | | 14 | 18 | | 15 | 13 | | 16 | 16 | | 17 | 7 | | 18 | 19 | | 19 | 7 | | 20 | 3 | | 21 | 6 | | 22 | 12 | | 23 | 10 | | 24 | 6 | | 25 | 18 | | 26 | 16 | | 27 | 7 | | 28 | 4 | | 29 | 10 | | 30 | 2 | | 31 | 2 | | 32 | 10 | | 33 | 6 | | 34 | 8 | | 35 | 4 | | 36 | 3 | | 37 | 10 | | 38 | 3 | | 39 | 11 | | 40 | 8 | | 41 | 8 | | 42 | 4 | | 43 | 21 | | 44 | 9 | | 45 | 3 | | 46 | 4 | | 47 | 22 | | 48 | 2 | | 49 | 9 |
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| 48.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.31313131313131315 | | totalSentences | 198 | | uniqueOpeners | 62 | |
| 55.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 121 | | matches | | 0 | "All belonged to officers, except" | | 1 | "Only a time and a" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 121 | | matches | | 0 | "His clothes looked expensive, though" | | 1 | "His eyes kept returning to" | | 2 | "His coat had no tear" | | 3 | "She crouched again, this time" | | 4 | "She looked at the tiles" | | 5 | "Their deep heels and squared" | | 6 | "She checked the soles of" | | 7 | "Their edges carried a chalky" | | 8 | "She pointed to the floor." | | 9 | "She held a hand above" | | 10 | "It had not flowed there." | | 11 | "Their edges had no dust" | | 12 | "He studied the symbols, then" | | 13 | "He looked towards the sealed" | | 14 | "It surfaced when he had" | | 15 | "He searched the coat pockets" | | 16 | "He passed it to the" | | 17 | "She moved to the old" | | 18 | "It did not point north." | | 19 | "It aimed at the wall" |
| | ratio | 0.248 | |
| 21.98% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 106 | | totalSentences | 121 | | matches | | 0 | "The forensic photographer froze with" | | 1 | "Harlow Quinn stepped over the" | | 2 | "The photographer looked down." | | 3 | "A grey smear crossed the" | | 4 | "Harlow crouched beside the body," | | 5 | "The smear matched the fine" | | 6 | "The sound travelled through the" | | 7 | "The abandoned station sat beneath" | | 8 | "A maintenance crew had found" | | 9 | "The entrance stairs rose to" | | 10 | "Harlow had counted the access" | | 11 | "Both had police officers at" | | 12 | "The dead man lay on" | | 13 | "His clothes looked expensive, though" | | 14 | "A narrow wound marked his" | | 15 | "Blood spread beneath his head" | | 16 | "DS Niall Patel stood by" | | 17 | "His eyes kept returning to" | | 18 | "Someone had scratched a row" | | 19 | "Each circle held a rough" |
| | ratio | 0.876 | |
| 41.32% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 121 | | matches | | 0 | "Before anyone moved, the wall" |
| | ratio | 0.008 | |
| 94.16% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 3 | | matches | | 0 | "The sound travelled through the station and came back thinner, as if something below the platform had answered." | | 1 | "Blood spread beneath his head in a dark, neat pool that stopped at the edge of his collar." | | 2 | "He passed it to the photographer, who placed it in a clear evidence sleeve." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 74 | | tagDensity | 0.176 | | leniency | 0.351 | | rawRatio | 0.077 | | effectiveRatio | 0.027 | |