| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1093 | | 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) | |
| 13.08% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1093 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "shattered" | | 1 | "weight" | | 2 | "maw" | | 3 | "chill" | | 4 | "echoed" | | 5 | "gloom" | | 6 | "scanning" | | 7 | "flickered" | | 8 | "silk" | | 9 | "pulsed" | | 10 | "rhythmic" | | 11 | "glinting" | | 12 | "vibrated" | | 13 | "resolve" | | 14 | "familiar" | | 15 | "pulse" |
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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 | 56 | | matches | (empty) | |
| 0.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 3 | | narrationSentences | 56 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 56 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1089 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 1089 | | uniqueNames | 14 | | maxNameDensity | 0.73 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 8 | | Raven | 1 | | Nest | 1 | | Morris | 2 | | Tube | 1 | | Veil | 1 | | Market | 2 | | Saint | 1 | | Christopher | 1 | | Herrera | 4 | | London | 1 | | Tomás | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Nest" | | 3 | "Morris" | | 4 | "Market" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Herrera" | | 8 | "Tomás" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | 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 | 1089 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 56 | | matches | (empty) | |
| 85.74% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 17 | | mean | 64.06 | | std | 28.83 | | cv | 0.45 | | sampleLengths | | 0 | 87 | | 1 | 78 | | 2 | 25 | | 3 | 81 | | 4 | 108 | | 5 | 32 | | 6 | 72 | | 7 | 22 | | 8 | 70 | | 9 | 32 | | 10 | 83 | | 11 | 21 | | 12 | 87 | | 13 | 71 | | 14 | 31 | | 15 | 92 | | 16 | 97 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 56 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 189 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 56 | | ratio | 0.071 | | matches | | 0 | "The Veil Market revealed itself in layers of gloom and color; merchants with faces obscured by silk veils sat behind stalls laden with jars of shimmering, viscous liquid and bundles of dried herbs that pulsed with a faint, rhythmic heartbeat." | | 1 | "She saw a merchant—a tall, spindly figure with fingers too long for its knuckles—gliding toward her, a curved blade glinting in its grip." | | 2 | "The choice hung in the space between her heartbeat and the next—to stand her ground in a place that defied all logic, or to pursue the man who held the one secret that could bridge the gap between human crime and the shadow that killed her partner." | | 3 | "With a swift movement, she holstered her weapon and reached into her pocket, pulling out a smooth, polished stone—a bone token she had scavenged from her partner's final locker." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1099 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.01364877161055505 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006369426751592357 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 56 | | echoCount | 0 | | echoWords | (empty) | |
| 97.32% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 56 | | mean | 19.45 | | std | 7.65 | | cv | 0.393 | | sampleLengths | | 0 | 21 | | 1 | 22 | | 2 | 27 | | 3 | 17 | | 4 | 22 | | 5 | 16 | | 6 | 21 | | 7 | 19 | | 8 | 5 | | 9 | 20 | | 10 | 9 | | 11 | 14 | | 12 | 29 | | 13 | 9 | | 14 | 20 | | 15 | 18 | | 16 | 22 | | 17 | 40 | | 18 | 28 | | 19 | 11 | | 20 | 21 | | 21 | 11 | | 22 | 19 | | 23 | 24 | | 24 | 18 | | 25 | 12 | | 26 | 10 | | 27 | 20 | | 28 | 21 | | 29 | 29 | | 30 | 11 | | 31 | 21 | | 32 | 16 | | 33 | 21 | | 34 | 23 | | 35 | 23 | | 36 | 21 | | 37 | 14 | | 38 | 21 | | 39 | 15 | | 40 | 14 | | 41 | 23 | | 42 | 5 | | 43 | 19 | | 44 | 47 | | 45 | 31 | | 46 | 12 | | 47 | 29 | | 48 | 11 | | 49 | 14 |
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| 52.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.39285714285714285 | | totalSentences | 56 | | uniqueOpeners | 22 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 77.14% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 56 | | matches | | 0 | "She kept her stride steady," | | 1 | "She reached the threshold and" | | 2 | "She remembered the empty stare" | | 3 | "She would not lose this" | | 4 | "She descended, the air turning" | | 5 | "Her boots clicked on metal" | | 6 | "You know better than to" | | 7 | "She stepped forward, the heel" | | 8 | "I have enough evidence to" | | 9 | "He stepped onto the tracks," | | 10 | "He gestured toward the far" | | 11 | "You keep walking, you forfeit" | | 12 | "She caught the scent of" | | 13 | "She saw a merchant—a tall," | | 14 | "She looked at her watch." | | 15 | "She took a breath, the" | | 16 | "She held it out towards" | | 17 | "She stepped forward again, crossing" | | 18 | "She ignored the voices now" | | 19 | "She was in the belly" |
| | ratio | 0.357 | |
| 40.36% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 56 | | matches | | 0 | "Rain lashed against the gray" | | 1 | "Detective Harlow Quinn tightened her" | | 2 | "The target moved with deceptive" | | 3 | "She kept her stride steady," | | 4 | "The silhouette rounded a corner," | | 5 | "Quinn accelerated, the salt-and-pepper cropped" | | 6 | "Water run-off from the gutters" | | 7 | "She reached the threshold and" | | 8 | "The voice echoed from the" | | 9 | "Quinn did not break her" | | 10 | "She remembered the empty stare" | | 11 | "She would not lose this" | | 12 | "She descended, the air turning" | | 13 | "Her boots clicked on metal" | | 14 | "The Veil Market revealed itself" | | 15 | "A man with curly dark" | | 16 | "You know better than to" | | 17 | "The last time someone chased" | | 18 | "Quinn kept her hand rock-steady," | | 19 | "Shadowy figures paused their haggling," |
| | ratio | 0.839 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 56 | | matches | | 0 | "If you want to see" | | 1 | "If you think a bit" |
| | ratio | 0.036 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 6 | | matches | | 0 | "Shadowy figures paused their haggling, turning to stare at her with eyes that reflected light in unnatural, feline slits." | | 1 | "The detective ignored the heat blooming in her gut, the instinctual warning that screamed for her to turn and run back to the surface." | | 2 | "He stepped onto the tracks, the third rail sparking with a sudden, violet discharge that illuminated the hollows of his cheeks." | | 3 | "He gestured toward the far end of the station, where the track bed descended into a tunnel choked with a thick, pulsating fog that defied the laws of airflow." | | 4 | "The detective bypassed Herrera, her gaze tracking the shadow moving behind her, the military precision of her stance holding the chaos at bay." | | 5 | "The second hand stuttered, then began to spin backward with a high-pitched, metallic whine that vibrated through her marrow." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |