| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 61 | | tagDensity | 0.016 | | leniency | 0.033 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.57% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2058 | | totalAiIsmAdverbs | 1 | | 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) | |
| 92.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2058 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "quivered" | | 1 | "trembled" | | 2 | "scanned" |
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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 | 188 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 188 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 248 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2057 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1504 | | uniqueNames | 10 | | maxNameDensity | 1.33 | | worstName | "Reed" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Reed" | | discoveredNames | | Camden | 1 | | Quinn | 1 | | London | 1 | | Colin | 1 | | Reed | 20 | | Harlow | 13 | | Underground | 1 | | Deptford | 1 | | Morris | 1 | | One | 4 |
| | persons | | 0 | "Camden" | | 1 | "Quinn" | | 2 | "Colin" | | 3 | "Reed" | | 4 | "Harlow" | | 5 | "Underground" | | 6 | "Morris" | | 7 | "One" |
| | places | | | globalScore | 0.835 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 113 | | 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 | 2057 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 248 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 135 | | mean | 15.24 | | std | 18.11 | | cv | 1.189 | | sampleLengths | | 0 | 14 | | 1 | 66 | | 2 | 70 | | 3 | 31 | | 4 | 5 | | 5 | 9 | | 6 | 2 | | 7 | 46 | | 8 | 5 | | 9 | 32 | | 10 | 7 | | 11 | 75 | | 12 | 2 | | 13 | 17 | | 14 | 3 | | 15 | 2 | | 16 | 1 | | 17 | 64 | | 18 | 9 | | 19 | 9 | | 20 | 67 | | 21 | 4 | | 22 | 3 | | 23 | 2 | | 24 | 5 | | 25 | 32 | | 26 | 4 | | 27 | 10 | | 28 | 7 | | 29 | 5 | | 30 | 48 | | 31 | 4 | | 32 | 6 | | 33 | 27 | | 34 | 2 | | 35 | 8 | | 36 | 77 | | 37 | 2 | | 38 | 47 | | 39 | 6 | | 40 | 6 | | 41 | 3 | | 42 | 7 | | 43 | 5 | | 44 | 3 | | 45 | 33 | | 46 | 12 | | 47 | 5 | | 48 | 8 | | 49 | 43 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 188 | | matches | | 0 | "been drawn" | | 1 | "been sealed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 242 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 248 | | ratio | 0.004 | | matches | | 0 | "Inside breast pocket—her gloved fingers paused, then produced a small brass compass with a green bloom of verdigris around the hinge." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1510 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 46 | | adverbRatio | 0.030463576158940398 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.003973509933774834 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 248 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 248 | | mean | 8.29 | | std | 7.93 | | cv | 0.956 | | sampleLengths | | 0 | 14 | | 1 | 23 | | 2 | 5 | | 3 | 8 | | 4 | 5 | | 5 | 5 | | 6 | 20 | | 7 | 8 | | 8 | 7 | | 9 | 16 | | 10 | 9 | | 11 | 15 | | 12 | 15 | | 13 | 15 | | 14 | 5 | | 15 | 11 | | 16 | 5 | | 17 | 9 | | 18 | 2 | | 19 | 46 | | 20 | 5 | | 21 | 18 | | 22 | 14 | | 23 | 7 | | 24 | 16 | | 25 | 2 | | 26 | 11 | | 27 | 6 | | 28 | 2 | | 29 | 13 | | 30 | 25 | | 31 | 2 | | 32 | 2 | | 33 | 15 | | 34 | 3 | | 35 | 2 | | 36 | 1 | | 37 | 7 | | 38 | 2 | | 39 | 13 | | 40 | 3 | | 41 | 2 | | 42 | 15 | | 43 | 10 | | 44 | 12 | | 45 | 9 | | 46 | 9 | | 47 | 2 | | 48 | 7 | | 49 | 17 |
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| 68.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.43951612903225806 | | totalSentences | 248 | | uniqueOpeners | 109 | |
| 62.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 160 | | matches | | 0 | "Only two compressed patches under" | | 1 | "More sat in the nostrils." | | 2 | "Then his eyes." |
| | ratio | 0.019 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 160 | | matches | | 0 | "His tie had slipped sideways." | | 1 | "He glanced around the station." | | 2 | "He pointed at clean rectangles" | | 3 | "He lay on his back" | | 4 | "Her leather watch creaked against" | | 5 | "She let her torch travel" | | 6 | "His right cuff sat higher" | | 7 | "Her gaze dropped to the" | | 8 | "She leaned closer." | | 9 | "She pointed with her pen." | | 10 | "It felt heavier than it" | | 11 | "She rose and turned in" | | 12 | "They hadn’t hosted a rave." | | 13 | "Her eyes settled on the" | | 14 | "He gave a tired snort." | | 15 | "She knelt again, touched a" | | 16 | "She straightened and pointed." | | 17 | "She crossed to the body" | | 18 | "They eased him into place." | | 19 | "She looked up at the" |
| | ratio | 0.238 | |
| 88.12% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 119 | | totalSentences | 160 | | matches | | 0 | "The old station sat beneath" | | 1 | "Harlow Quinn came down the" | | 2 | "Rust flaked beneath her palm." | | 3 | "Water tapped somewhere below, steady" | | 4 | "Halfway down, the air changed." | | 5 | "The city smell thinned out." | | 6 | "Police tape ran between two" | | 7 | "A woman in a 1970s" | | 8 | "A crooked enamel sign still" | | 9 | "DS Colin Reed stood near" | | 10 | "His tie had slipped sideways." | | 11 | "Harlow stepped under the tape" | | 12 | "He glanced around the station." | | 13 | "He pointed at clean rectangles" | | 14 | "Harlow stopped three paces from" | | 15 | "He lay on his back" | | 16 | "Blood had soaked through his" | | 17 | "Her leather watch creaked against" | | 18 | "She let her torch travel" | | 19 | "Soles clean except for a" |
| | ratio | 0.744 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 160 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 1 | | matches | | 0 | "A single print emerged in the skim of dust beside the arch, almost erased, narrow heel, deep toe, as if the person had pivoted hard." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |