| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 98.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2581 | | totalAiIsmAdverbs | 1 | | 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) | |
| 92.25% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2581 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "lurched" | | 1 | "flickered" | | 2 | "absolutely" | | 3 | "pulsed" |
| |
| 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 | 242 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 242 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 353 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2580 | | 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 | 128 | | wordCount | 2044 | | uniqueNames | 27 | | maxNameDensity | 2.54 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Quinn" | | discoveredNames | | Wardour | 1 | | Street | 2 | | Detective | 1 | | Harlow | 1 | | Quinn | 52 | | Tomás | 1 | | Herrera | 33 | | Raven | 3 | | Nest | 3 | | Spanish | 1 | | Shaftesbury | 1 | | Avenue | 1 | | Morris | 5 | | Braids | 1 | | Camden | 1 | | High | 1 | | Prague | 1 | | Sorn | 1 | | Saint | 1 | | Christopher | 1 | | West | 1 | | End | 1 | | London | 1 | | Rain | 3 | | Blood | 4 | | One | 3 | | Three | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Raven" | | 5 | "Nest" | | 6 | "Morris" | | 7 | "Braids" | | 8 | "Sorn" | | 9 | "Saint" | | 10 | "Christopher" | | 11 | "Rain" | | 12 | "Blood" | | 13 | "One" |
| | places | | 0 | "Wardour" | | 1 | "Street" | | 2 | "Shaftesbury" | | 3 | "Avenue" | | 4 | "Camden" | | 5 | "High" | | 6 | "Prague" | | 7 | "West" | | 8 | "End" | | 9 | "London" |
| | globalScore | 0.228 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 161 | | 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 | 2580 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 353 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 231 | | mean | 11.17 | | std | 12.1 | | cv | 1.083 | | sampleLengths | | 0 | 37 | | 1 | 1 | | 2 | 3 | | 3 | 4 | | 4 | 50 | | 5 | 6 | | 6 | 3 | | 7 | 28 | | 8 | 10 | | 9 | 3 | | 10 | 43 | | 11 | 3 | | 12 | 4 | | 13 | 3 | | 14 | 10 | | 15 | 2 | | 16 | 2 | | 17 | 49 | | 18 | 4 | | 19 | 54 | | 20 | 8 | | 21 | 5 | | 22 | 5 | | 23 | 39 | | 24 | 2 | | 25 | 3 | | 26 | 9 | | 27 | 4 | | 28 | 5 | | 29 | 15 | | 30 | 33 | | 31 | 3 | | 32 | 2 | | 33 | 6 | | 34 | 11 | | 35 | 5 | | 36 | 6 | | 37 | 26 | | 38 | 5 | | 39 | 2 | | 40 | 38 | | 41 | 22 | | 42 | 1 | | 43 | 12 | | 44 | 16 | | 45 | 4 | | 46 | 17 | | 47 | 2 | | 48 | 7 | | 49 | 3 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 242 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 360 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 2 | | flaggedSentences | 3 | | totalSentences | 353 | | ratio | 0.008 | | matches | | 0 | "Quinn caught fragments—names, pleas, a child counting backwards." | | 1 | "Herrera grunted as the impact tore something inside him; fresh blood slid over his waistband." | | 2 | "One carried a hooked pole; the other dragged a chain that disappeared beneath a stall." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1577 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.015218769816106531 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0025364616360177552 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 353 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 353 | | mean | 7.31 | | std | 5.09 | | cv | 0.696 | | sampleLengths | | 0 | 16 | | 1 | 21 | | 2 | 1 | | 3 | 3 | | 4 | 4 | | 5 | 13 | | 6 | 10 | | 7 | 6 | | 8 | 21 | | 9 | 6 | | 10 | 2 | | 11 | 1 | | 12 | 17 | | 13 | 11 | | 14 | 10 | | 15 | 3 | | 16 | 7 | | 17 | 10 | | 18 | 2 | | 19 | 8 | | 20 | 7 | | 21 | 9 | | 22 | 3 | | 23 | 4 | | 24 | 3 | | 25 | 5 | | 26 | 5 | | 27 | 2 | | 28 | 2 | | 29 | 28 | | 30 | 21 | | 31 | 4 | | 32 | 33 | | 33 | 6 | | 34 | 4 | | 35 | 11 | | 36 | 8 | | 37 | 5 | | 38 | 5 | | 39 | 11 | | 40 | 9 | | 41 | 12 | | 42 | 7 | | 43 | 2 | | 44 | 3 | | 45 | 9 | | 46 | 4 | | 47 | 5 | | 48 | 3 | | 49 | 12 |
| |
| 51.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.32386363636363635 | | totalSentences | 352 | | uniqueOpeners | 114 | |
| 29.24% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 228 | | matches | | 0 | "Then he had bolted." | | 1 | "Officially last seen six months" |
| | ratio | 0.009 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 228 | | matches | | 0 | "He glanced back." | | 1 | "Her coat dragged at her" | | 2 | "She slapped the bonnet of" | | 3 | "He had frozen when he" | | 4 | "Its walls swallowed evidence." | | 5 | "Its patrons forgot names, faces" | | 6 | "His jumper had ridden up," | | 7 | "His Spanish accent sharpened the" | | 8 | "He landed badly." | | 9 | "His right leg buckled, but" | | 10 | "She shut it out and" | | 11 | "He shouldered through a fire" | | 12 | "He looked back again." | | 13 | "His hand tightened over his" | | 14 | "He cut between cars stalled" | | 15 | "Its rider cursed and raised" | | 16 | "She planted a palm on" | | 17 | "His blood trail had thickened." | | 18 | "Her radio hissed beneath her" | | 19 | "She pressed the transmit switch" |
| | ratio | 0.184 | |
| 27.98% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 197 | | totalSentences | 228 | | matches | | 0 | "He glanced back." | | 1 | "That cost him ground." | | 2 | "Quinn clipped a shoulder, caught" | | 3 | "Water ran from her cropped" | | 4 | "Her coat dragged at her" | | 5 | "Herrera wore no jacket, only" | | 6 | "Blood marked every third paving" | | 7 | "A bus hauled across the" | | 8 | "Quinn heard a horn, then" | | 9 | "She slapped the bonnet of" | | 10 | "The driver’s protest vanished beneath" | | 11 | "Quinn reached the opposite pavement" | | 12 | "A kebab shop burned white" | | 13 | "The rider shook his helmet." | | 14 | "He had frozen when he" | | 15 | "The Raven’s Nest sat behind" | | 16 | "Quinn had raided the place" | | 17 | "Its walls swallowed evidence." | | 18 | "Its patrons forgot names, faces" | | 19 | "This time she had seen" |
| | ratio | 0.864 | |
| 21.93% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 228 | | matches | | 0 | "Even at a distance, Quinn" |
| | ratio | 0.004 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 79 | | technicalSentenceCount | 4 | | matches | | 0 | "The Raven’s Nest sat behind her now, its green raven buzzing over the entrance, the old maps and black-and-white photographs inside left under the care of two u…" | | 1 | "Herrera’s file contained no violence beyond the knife attack that had carved a scar along his left forearm." | | 2 | "Lanterns floated without chains above tables piled with stoppered bottles, silver cages and folded skins that shivered in the stale underground wind." | | 3 | "One carried a hooked pole; the other dragged a chain that disappeared beneath a stall." |
| |
| 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 | |