| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.229 | | leniency | 0.457 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.35% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1307 | | totalAiIsmAdverbs | 2 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
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| | highlights | | 0 | "slightly" | | 1 | "deliberately" |
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| 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) | |
| 65.57% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1307 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "navigated" | | 1 | "silk" | | 2 | "etched" | | 3 | "magnetic" | | 4 | "standard" | | 5 | "pristine" | | 6 | "chill" |
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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 | 90 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 90 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1318 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 77.46% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 896 | | uniqueNames | 9 | | maxNameDensity | 1.45 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 13 | | Sinclair | 7 | | Styrofoam | 1 | | Habit | 1 | | Soho | 1 | | London | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sinclair" | | 3 | "Morris" |
| | places | | | globalScore | 0.775 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 1318 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 25.84 | | std | 20.02 | | cv | 0.775 | | sampleLengths | | 0 | 62 | | 1 | 50 | | 2 | 1 | | 3 | 49 | | 4 | 37 | | 5 | 43 | | 6 | 4 | | 7 | 61 | | 8 | 67 | | 9 | 10 | | 10 | 5 | | 11 | 15 | | 12 | 49 | | 13 | 6 | | 14 | 5 | | 15 | 4 | | 16 | 7 | | 17 | 11 | | 18 | 65 | | 19 | 27 | | 20 | 35 | | 21 | 4 | | 22 | 30 | | 23 | 24 | | 24 | 4 | | 25 | 52 | | 26 | 42 | | 27 | 11 | | 28 | 5 | | 29 | 23 | | 30 | 15 | | 31 | 4 | | 32 | 14 | | 33 | 49 | | 34 | 3 | | 35 | 28 | | 36 | 45 | | 37 | 15 | | 38 | 43 | | 39 | 12 | | 40 | 63 | | 41 | 17 | | 42 | 9 | | 43 | 28 | | 44 | 7 | | 45 | 35 | | 46 | 10 | | 47 | 51 | | 48 | 19 | | 49 | 11 |
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| 93.57% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 90 | | matches | | 0 | "been sealed" | | 1 | "was etched" | | 2 | "been told" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 145 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 117 | | ratio | 0.051 | | matches | | 0 | "Petechial haemorrhaging — tiny red spots — speckled the skin around his eyes and along the temples." | | 1 | "The concrete platform was cracked and stained, but near the body — specifically near the man's left side — she noticed something." | | 2 | "It caught the torchlight and threw it back in colours that didn't belong underground — a shimmer of green-gold that faded to nothing at the edges." | | 3 | "Its casing carried a greenish patina, and the face was etched with symbols she didn't recognise — not navigational markings, not cardinal directions." | | 4 | "On the back, a maker's mark — a symbol she'd seen before." | | 5 | "The petechial haemorrhaging — a sign of asphyxiation, not blunt force trauma." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 833 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.01920768307322929 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006002400960384154 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 11.26 | | std | 9 | | cv | 0.799 | | sampleLengths | | 0 | 26 | | 1 | 36 | | 2 | 22 | | 3 | 16 | | 4 | 12 | | 5 | 1 | | 6 | 22 | | 7 | 27 | | 8 | 14 | | 9 | 1 | | 10 | 18 | | 11 | 4 | | 12 | 22 | | 13 | 21 | | 14 | 4 | | 15 | 11 | | 16 | 50 | | 17 | 5 | | 18 | 12 | | 19 | 9 | | 20 | 14 | | 21 | 3 | | 22 | 4 | | 23 | 20 | | 24 | 2 | | 25 | 8 | | 26 | 5 | | 27 | 15 | | 28 | 5 | | 29 | 3 | | 30 | 17 | | 31 | 7 | | 32 | 17 | | 33 | 6 | | 34 | 5 | | 35 | 4 | | 36 | 7 | | 37 | 11 | | 38 | 7 | | 39 | 16 | | 40 | 7 | | 41 | 6 | | 42 | 3 | | 43 | 8 | | 44 | 3 | | 45 | 15 | | 46 | 14 | | 47 | 1 | | 48 | 6 | | 49 | 5 |
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| 64.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.4358974358974359 | | totalSentences | 117 | | uniqueOpeners | 51 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 79 | | matches | | 0 | "He held a Styrofoam cup" | | 1 | "His eyes were open, fixed" | | 2 | "She leaned closer and tilted" | | 3 | "She sat back on her" | | 4 | "She played her torch along" | | 5 | "She returned to the body" | | 6 | "She checked beneath the nails." | | 7 | "She walked a slow circle" | | 8 | "She crouched again and brought" | | 9 | "It caught the torchlight and" | | 10 | "She ignored him and shifted" | | 11 | "She opened the man's overcoat" | | 12 | "She felt along the lining." | | 13 | "She pressed the fabric between" | | 14 | "Her fingers closed around something" | | 15 | "She withdrew it." | | 16 | "Its casing carried a greenish" | | 17 | "She closed her fingers around" | | 18 | "She thought of Morris." | | 19 | "She turned and walked back" |
| | ratio | 0.253 | |
| 54.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 79 | | matches | | 0 | "The body lay at the" | | 1 | "Water dripped from the curved" | | 2 | "Detective Harlow Quinn ducked under" | | 3 | "A forensic tech knelt beside" | | 4 | "He held a Styrofoam cup" | | 5 | "Quinn stopped three metres from" | | 6 | "Sinclair gestured toward the body" | | 7 | "Sinclair shrugged, a deliberate rolling" | | 8 | "Quinn finally approached the body." | | 9 | "The man lay on his" | | 10 | "His eyes were open, fixed" | | 11 | "Wool overcoat, charcoal." | | 12 | "Leather shoes, not trainers." | | 13 | "The kind of outfit you'd" | | 14 | "The forensic tech shifted to" | | 15 | "Quinn studied the man's face." | | 16 | "She leaned closer and tilted" | | 17 | "She sat back on her" | | 18 | "Quinn stood and walked to" | | 19 | "The metal teeth of the" |
| | ratio | 0.81 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 20.41% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 6 | | matches | | 0 | "Water dripped from the curved ceiling of the Tube station, pooling in the grime between cracked tiles, and the air carried the particular staleness of a place t…" | | 1 | "Clean-shaven, dark hair, and dressed in clothes that didn't match the urban explorer profile." | | 2 | "No bruising along the jaw or forehead that would indicate a face-first fall down a decommissioned escalator." | | 3 | "It caught the torchlight and threw it back in colours that didn't belong underground — a shimmer of green-gold that faded to nothing at the edges." | | 4 | "The needle continued its restless rotation, as if pulled in multiple directions at once." | | 5 | "A case that had cost DS Morris his life in circumstances no one would explain to her, circumstances that had left her with questions that rotted in her chest li…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |