| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "She stepped carefully [carefully]" |
| | dialogueSentences | 42 | | tagDensity | 0.381 | | leniency | 0.762 | | rawRatio | 0.063 | | effectiveRatio | 0.048 | |
| 92.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1259 | | 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) | |
| 8.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1259 | | totalAiIsms | 23 | | found | | | highlights | | 0 | "echoing" | | 1 | "traced" | | 2 | "jaw clenched" | | 3 | "furrowed" | | 4 | "scanned" | | 5 | "flickered" | | 6 | "etched" | | 7 | "trembled" | | 8 | "racing" | | 9 | "tracing" | | 10 | "dancing" | | 11 | "measured" | | 12 | "standard" | | 13 | "flicked" | | 14 | "footsteps" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 110 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 110 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 136 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1248 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 880 | | uniqueNames | 8 | | maxNameDensity | 3.3 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 29 | | Camden | 1 | | Tube | 1 | | Kowalski | 1 | | Silver | 1 | | Chalk | 1 | | Eva | 23 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.801 | | wordCount | 1248 | | matches | | 0 | "not north but toward the tunnel mouth beyond the platform" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 136 | | matches | (empty) | |
| 75.26% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 29.02 | | std | 12 | | cv | 0.413 | | sampleLengths | | 0 | 53 | | 1 | 48 | | 2 | 48 | | 3 | 37 | | 4 | 33 | | 5 | 35 | | 6 | 27 | | 7 | 30 | | 8 | 48 | | 9 | 18 | | 10 | 43 | | 11 | 22 | | 12 | 41 | | 13 | 36 | | 14 | 35 | | 15 | 6 | | 16 | 31 | | 17 | 32 | | 18 | 60 | | 19 | 30 | | 20 | 38 | | 21 | 24 | | 22 | 32 | | 23 | 17 | | 24 | 14 | | 25 | 28 | | 26 | 14 | | 27 | 17 | | 28 | 15 | | 29 | 27 | | 30 | 13 | | 31 | 39 | | 32 | 30 | | 33 | 24 | | 34 | 18 | | 35 | 34 | | 36 | 26 | | 37 | 13 | | 38 | 11 | | 39 | 28 | | 40 | 19 | | 41 | 31 | | 42 | 23 |
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| 98.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 110 | | matches | | 0 | "been killed" | | 1 | "been rubbed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 173 | | matches | (empty) | |
| 16.81% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 1 | | flaggedSentences | 6 | | totalSentences | 136 | | ratio | 0.044 | | matches | | 0 | "The station lights had long since died; only a single LED lantern dangled from a low beam, casting a harsh pool of pale blue." | | 1 | "She frowned, lifted a corner of the victim’s coat to reveal a jagged wound—uncommonly clean, as if carved with a surgeon’s knife." | | 2 | "Dark smudges traced under eyelids—residue from some powder, perhaps." | | 3 | "Quinn slid a latex-gloved finger beneath it and peeled it free—a scrap of parchment, edges singed." | | 4 | "Last month, three paranormal disturbances across the city—strange lights, missing persons, unexplained power failures." | | 5 | "Footsteps sounded behind them—slow, echoing across the tracks." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 888 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.02027027027027027 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007882882882882882 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 136 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 136 | | mean | 9.18 | | std | 5.42 | | cv | 0.591 | | sampleLengths | | 0 | 20 | | 1 | 9 | | 2 | 24 | | 3 | 9 | | 4 | 14 | | 5 | 9 | | 6 | 16 | | 7 | 10 | | 8 | 6 | | 9 | 22 | | 10 | 5 | | 11 | 5 | | 12 | 19 | | 13 | 6 | | 14 | 12 | | 15 | 8 | | 16 | 15 | | 17 | 10 | | 18 | 11 | | 19 | 2 | | 20 | 17 | | 21 | 5 | | 22 | 3 | | 23 | 24 | | 24 | 3 | | 25 | 22 | | 26 | 5 | | 27 | 6 | | 28 | 8 | | 29 | 10 | | 30 | 5 | | 31 | 9 | | 32 | 8 | | 33 | 2 | | 34 | 5 | | 35 | 13 | | 36 | 5 | | 37 | 9 | | 38 | 4 | | 39 | 9 | | 40 | 16 | | 41 | 8 | | 42 | 11 | | 43 | 3 | | 44 | 4 | | 45 | 7 | | 46 | 26 | | 47 | 4 | | 48 | 3 | | 49 | 20 |
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| 67.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4117647058823529 | | totalSentences | 136 | | uniqueOpeners | 56 | |
| 32.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 103 | | matches | | | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 103 | | matches | | 0 | "She frowned, lifted a corner" | | 1 | "She jotted notes into a" | | 2 | "She swiped her glove across" | | 3 | "She stood, movements precise as" | | 4 | "She scanned the platform edge" | | 5 | "Her voice tightened" | | 6 | "She lifted the parchment to" | | 7 | "She reached to snatch the" | | 8 | "She swivelled the compass under" | | 9 | "She flourished her hand toward" | | 10 | "She knelt beside the victim" | | 11 | "She tapped a smudge where" | | 12 | "She slid them back on" | | 13 | "She pointed her torch into" | | 14 | "She stepped carefully over the" | | 15 | "She crouched and pressed the" | | 16 | "She dropped the notebook back" |
| | ratio | 0.165 | |
| 47.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 103 | | matches | | 0 | "Detective Harlow Quinn climbed down" | | 1 | "The station lights had long" | | 2 | "Water pooled beneath the tracks," | | 3 | "Quinn’s leather watch tapped against" | | 4 | "A body lay face‐down, limbs" | | 5 | "The blood had pooled around" | | 6 | "A uniformed constable hovered near" | | 7 | "Hands shaking, he avoided Quinn’s" | | 8 | "She frowned, lifted a corner" | | 9 | "Eva Kowalski stood off to" | | 10 | "She jotted notes into a" | | 11 | "Eva murmured, pointing to the" | | 12 | "Quinn traced the chalk with" | | 13 | "She swiped her glove across" | | 14 | "Chalk dust clung to leather." | | 15 | "Eva’s jaw clenched." | | 16 | "Quinn’s brow furrowed." | | 17 | "She stood, movements precise as" | | 18 | "A drip splashed onto the" | | 19 | "The body shifted as water" |
| | ratio | 0.825 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 103 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 1 | | matches | | 0 | "She frowned, lifted a corner of the victim’s coat to reveal a jagged wound—uncommonly clean, as if carved with a surgeon’s knife." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 2 | | matches | | 0 | "She reached, but Quinn’s fingers closed over it" | | 1 | "Quinn said, voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "Eva murmured (murmur)" | | 1 | "Eva whispered (whisper)" |
| | dialogueSentences | 42 | | tagDensity | 0.095 | | leniency | 0.19 | | rawRatio | 0.5 | | effectiveRatio | 0.095 | |