| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.529 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.77% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1084 | | totalAiIsmAdverbs | 2 | | 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) | |
| 58.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1084 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "etched" | | 1 | "silence" | | 2 | "weight" | | 3 | "traced" | | 4 | "familiar" | | 5 | "trembled" | | 6 | "magnetic" | | 7 | "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 | 70 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 70 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1084 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 88.68% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 897 | | uniqueNames | 10 | | maxNameDensity | 1.23 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Brennan" | | discoveredNames | | Town | 1 | | Tube | 1 | | Victorian | 1 | | Brennan | 9 | | Quinn | 11 | | Italian | 1 | | Savile | 1 | | Row | 1 | | Morris | 1 | | Tuesday | 1 |
| | persons | | 0 | "Brennan" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | | globalScore | 0.887 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 15.50% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.845 | | wordCount | 1084 | | matches | | 0 | "not empty but occupied, waiting" | | 1 | "not north, but downward, through the rail, through the earth, towards somet" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 78 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 36.13 | | std | 19.17 | | cv | 0.531 | | sampleLengths | | 0 | 21 | | 1 | 55 | | 2 | 32 | | 3 | 17 | | 4 | 58 | | 5 | 61 | | 6 | 3 | | 7 | 48 | | 8 | 12 | | 9 | 26 | | 10 | 18 | | 11 | 69 | | 12 | 61 | | 13 | 44 | | 14 | 29 | | 15 | 51 | | 16 | 57 | | 17 | 11 | | 18 | 9 | | 19 | 65 | | 20 | 4 | | 21 | 43 | | 22 | 33 | | 23 | 48 | | 24 | 30 | | 25 | 30 | | 26 | 16 | | 27 | 53 | | 28 | 37 | | 29 | 43 |
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| 95.24% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 70 | | matches | | 0 | "was turned" | | 1 | "been placed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 148 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 78 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 901 | | adjectiveStacks | 1 | | stackExamples | | 0 | "far above yellow crime" |
| | adverbCount | 28 | | adverbRatio | 0.03107658157602664 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.005549389567147614 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 13.9 | | std | 9.71 | | cv | 0.699 | | sampleLengths | | 0 | 8 | | 1 | 13 | | 2 | 12 | | 3 | 11 | | 4 | 13 | | 5 | 14 | | 6 | 5 | | 7 | 2 | | 8 | 21 | | 9 | 9 | | 10 | 17 | | 11 | 10 | | 12 | 35 | | 13 | 13 | | 14 | 2 | | 15 | 20 | | 16 | 25 | | 17 | 14 | | 18 | 3 | | 19 | 33 | | 20 | 15 | | 21 | 4 | | 22 | 8 | | 23 | 15 | | 24 | 11 | | 25 | 3 | | 26 | 11 | | 27 | 4 | | 28 | 9 | | 29 | 9 | | 30 | 51 | | 31 | 2 | | 32 | 6 | | 33 | 21 | | 34 | 3 | | 35 | 3 | | 36 | 26 | | 37 | 6 | | 38 | 38 | | 39 | 16 | | 40 | 13 | | 41 | 9 | | 42 | 11 | | 43 | 5 | | 44 | 20 | | 45 | 6 | | 46 | 9 | | 47 | 18 | | 48 | 30 | | 49 | 11 |
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| 68.38% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.44871794871794873 | | totalSentences | 78 | | uniqueOpeners | 35 | |
| 53.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 62 | | matches | | 0 | "Too small for decapitation-level trauma," |
| | ratio | 0.016 | |
| 84.52% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 62 | | matches | | 0 | "She jerked her chin downward." | | 1 | "She pulled on gloves, not" | | 2 | "His face was turned away," | | 3 | "His neck snapped back at" | | 4 | "His right hand clutched a" | | 5 | "She leaned closer." | | 6 | "She shrugged, letting the silence" | | 7 | "She walked the perimeter, boots" | | 8 | "She knelt near the body" | | 9 | "His coat was expensive, Savile" | | 10 | "She traced the beam along" | | 11 | "She leaned closer, ignoring the" | | 12 | "His lips were blue, not" | | 13 | "His eyes, wide and fixed" | | 14 | "she said, not turning" | | 15 | "She turned back to the" | | 16 | "His leather gloves showed no" | | 17 | "His polished boots faced north," | | 18 | "she said, more to herself" | | 19 | "She straightened, her bearing carrying" |
| | ratio | 0.339 | |
| 24.52% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 62 | | matches | | 0 | "Quinn pushed through the crowd" | | 1 | "The smell of old electricity" | | 2 | "Camden Town's dead Tube tunnel" | | 3 | "Water dripped from arched Victorian" | | 4 | "Forensics shuffled in the mud" | | 5 | "DS Brennan caught her eye" | | 6 | "She jerked her chin downward." | | 7 | "Mud sucked at her boots" | | 8 | "She pulled on gloves, not" | | 9 | "The body lay twenty feet" | | 10 | "A tall, lean man in" | | 11 | "His face was turned away," | | 12 | "The rail had sheared through" | | 13 | "His neck snapped back at" | | 14 | "His right hand clutched a" | | 15 | "She leaned closer." | | 16 | "A small brass compass rested" | | 17 | "Verdigris coated every ridge of" | | 18 | "The words came out flatter" | | 19 | "Brennan hovered, notebook in hand," |
| | ratio | 0.871 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 12 | | matches | | 0 | "Forensics shuffled in the mud with torches, tracking footprints that led precisely nowhere." | | 1 | "Mud sucked at her boots with each step, the kind of thick, ancient sludge that clung to leather regardless of polish." | | 2 | "The body lay twenty feet under an overturned maintenance trolley that smelled of rust and burnt rubber." | | 3 | "A tall, lean man in a charcoal wool coat with horn buttons, leather gloves that had never seen manual labour, and boots polished to a mirror shine that now refl…" | | 4 | "His right hand clutched a brass object that glinted green with age and corrosion." | | 5 | "A small brass compass rested in his dead grip, its face etched with symbols that hurt her eyes if she stared too long, its needle still, dead, pointing north wi…" | | 6 | "His coat was expensive, Savile Row perhaps, and beneath the mud at the collar she spotted a bone token, carved with symbols that matched those on the compass fa…" | | 7 | "But beneath his left eyelid, a faint silver marking traced patterns she recognised from a case three years prior, from DS Morris's final report that had never s…" | | 8 | "Five points, arranged with geometric precision, each the size of a grown man's spread hand, pressed into the brick with force that had cracked mortar." | | 9 | "She straightened, her bearing carrying that military precision that made younger officers stand straighter without knowing why." | | 10 | "She prised the compass from his dead fingers, feeling the brass hum with a cold that had nothing to do with tunnel temperature." | | 11 | "The compass needle trembled, then snapped, pointing straight at Quinn's chest with magnetic insistence that defied every law she trusted." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 4 | | matches | | 0 | "Brennan continued, voice carrying that particular confidence of the recently trained" | | 1 | "she said, not turning" | | 2 | "Quinn said, her voice low, carrying in the tunnel's hollow acoustics" | | 3 | "she said, more to herself now" |
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| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "Brennan continued (continue)" |
| | dialogueSentences | 17 | | tagDensity | 0.353 | | leniency | 0.706 | | rawRatio | 0.167 | | effectiveRatio | 0.118 | |