| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 95 | | tagDensity | 0.032 | | leniency | 0.063 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1826 | | 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) | |
| 89.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1826 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "electric" | | 1 | "scanned" | | 2 | "measured" | | 3 | "flickered" |
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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 | 162 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 162 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 254 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1826 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 59.71% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 61 | | wordCount | 1329 | | uniqueNames | 10 | | maxNameDensity | 1.81 | | worstName | "Vale" | | maxWindowNameDensity | 3 | | worstWindowName | "Vale" | | discoveredNames | | Quinn | 21 | | Leon | 1 | | Vale | 24 | | Metropolitan | 1 | | Police | 1 | | Venn | 1 | | Mara | 7 | | British | 1 | | Museum | 1 | | One | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Leon" | | 2 | "Vale" | | 3 | "Venn" | | 4 | "Mara" | | 5 | "Museum" | | 6 | "One" |
| | places | | | globalScore | 0.597 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 108 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared dark at the toe and faded towards the heel" |
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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 | 1826 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 254 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 177 | | mean | 10.32 | | std | 11.96 | | cv | 1.159 | | sampleLengths | | 0 | 11 | | 1 | 30 | | 2 | 7 | | 3 | 2 | | 4 | 29 | | 5 | 6 | | 6 | 3 | | 7 | 3 | | 8 | 2 | | 9 | 4 | | 10 | 15 | | 11 | 4 | | 12 | 39 | | 13 | 35 | | 14 | 7 | | 15 | 7 | | 16 | 38 | | 17 | 6 | | 18 | 2 | | 19 | 4 | | 20 | 6 | | 21 | 8 | | 22 | 12 | | 23 | 6 | | 24 | 58 | | 25 | 8 | | 26 | 47 | | 27 | 13 | | 28 | 5 | | 29 | 3 | | 30 | 2 | | 31 | 4 | | 32 | 2 | | 33 | 4 | | 34 | 7 | | 35 | 6 | | 36 | 4 | | 37 | 3 | | 38 | 5 | | 39 | 3 | | 40 | 2 | | 41 | 6 | | 42 | 4 | | 43 | 1 | | 44 | 10 | | 45 | 4 | | 46 | 5 | | 47 | 32 | | 48 | 24 | | 49 | 40 |
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| 98.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 162 | | matches | | 0 | "been pulled" | | 1 | "been bricked" | | 2 | "been drawn" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 214 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 254 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1334 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.019490254872563718 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0014992503748125937 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 254 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 254 | | mean | 7.19 | | std | 5.3 | | cv | 0.737 | | sampleLengths | | 0 | 11 | | 1 | 22 | | 2 | 8 | | 3 | 7 | | 4 | 2 | | 5 | 10 | | 6 | 19 | | 7 | 6 | | 8 | 3 | | 9 | 3 | | 10 | 2 | | 11 | 4 | | 12 | 5 | | 13 | 10 | | 14 | 4 | | 15 | 9 | | 16 | 7 | | 17 | 13 | | 18 | 5 | | 19 | 5 | | 20 | 8 | | 21 | 13 | | 22 | 4 | | 23 | 10 | | 24 | 7 | | 25 | 7 | | 26 | 4 | | 27 | 24 | | 28 | 7 | | 29 | 3 | | 30 | 6 | | 31 | 2 | | 32 | 4 | | 33 | 6 | | 34 | 8 | | 35 | 12 | | 36 | 6 | | 37 | 16 | | 38 | 13 | | 39 | 13 | | 40 | 16 | | 41 | 8 | | 42 | 4 | | 43 | 20 | | 44 | 12 | | 45 | 11 | | 46 | 13 | | 47 | 5 | | 48 | 3 | | 49 | 2 |
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| 49.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.32677165354330706 | | totalSentences | 254 | | uniqueOpeners | 83 | |
| 22.08% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 151 | | matches | | 0 | "Somewhere beyond the ticket hall," |
| | ratio | 0.007 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 151 | | matches | | 0 | "She drew her torch and" | | 1 | "His torch beam slid over" | | 2 | "His broad face tightened, but" | | 3 | "She checked her leather watch," | | 4 | "Her left wrist remained steady." | | 5 | "They stood near the ticket" | | 6 | "It also bore three small" | | 7 | "He led her through the" | | 8 | "Its door stood open." | | 9 | "She wore a green wool" | | 10 | "Her torch picked out the" | | 11 | "She wore no jewellery except" | | 12 | "Her body had settled there" | | 13 | "It showed the legs of" | | 14 | "He looked towards the ceiling," | | 15 | "Its drawers had been pulled" | | 16 | "She lifted it with a" | | 17 | "He crouched and studied the" | | 18 | "He did not answer." | | 19 | "It gleamed under the torch," |
| | ratio | 0.205 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 140 | | totalSentences | 151 | | matches | | 0 | "Harlow Quinn caught the falling" | | 1 | "The rusted grille shuddered in" | | 2 | "She drew her torch and" | | 3 | "DS Leon Vale ducked beneath" | | 4 | "His torch beam slid over" | | 5 | "Vale glanced at the grille." | | 6 | "His broad face tightened, but" | | 7 | "Quinn looked at the sealed" | | 8 | "The grille had no draught" | | 9 | "She checked her leather watch," | | 10 | "The dial’s hands showed 02:17." | | 11 | "Her left wrist remained steady." | | 12 | "Vale had arrived first with" | | 13 | "They stood near the ticket" | | 14 | "The other guarded a narrow" | | 15 | "The tape bore the Metropolitan" | | 16 | "It also bore three small" | | 17 | "Quinn approached the archway." | | 18 | "The prints sat on the" | | 19 | "The nearest officer had not" |
| | ratio | 0.927 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 151 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 2 | | matches | | 0 | "The prints sat on the tape’s upper edge, each finger long and pointed, as if a child had pressed a tar-coated hand against it." | | 1 | "The prints began beside a cracked column and continued towards the staircase that led to the sealed street entrance." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 95 | | tagDensity | 0.032 | | leniency | 0.063 | | rawRatio | 0.333 | | effectiveRatio | 0.021 | |