| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.091 | | leniency | 0.182 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1507 | | 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) | |
| 36.96% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1507 | | totalAiIsms | 19 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | word | "practiced ease" | | count | 1 |
| | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "clandestine" | | 1 | "measured" | | 2 | "rhythmic" | | 3 | "chaotic" | | 4 | "treacherous" | | 5 | "shattered" | | 6 | "weight" | | 7 | "structure" | | 8 | "echoes" | | 9 | "echoed" | | 10 | "shimmered" | | 11 | "practiced ease" | | 12 | "fractured" | | 13 | "etched" | | 14 | "loomed" | | 15 | "absolutely" | | 16 | "pulse" | | 17 | "depths" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 128 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 128 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 138 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1496 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 69 | | wordCount | 1417 | | uniqueNames | 25 | | maxNameDensity | 1.41 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Herrera" | | discoveredNames | | London | 3 | | Camden | 4 | | Herrera | 18 | | Greek | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Leicester | 1 | | Square | 1 | | Northern | 1 | | Harlow | 20 | | Saint | 1 | | Christopher | 1 | | Spanish | 1 | | Seville | 1 | | Spain | 1 | | Regent | 1 | | Canal | 1 | | Soho | 1 | | Morris | 2 | | Victorian | 1 | | Veil | 1 | | Market | 1 | | Tube | 1 | | Tap | 3 |
| | persons | | 0 | "Herrera" | | 1 | "Raven" | | 2 | "Harlow" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Morris" | | 6 | "Market" |
| | places | | 0 | "London" | | 1 | "Camden" | | 2 | "Greek" | | 3 | "Street" | | 4 | "Leicester" | | 5 | "Seville" | | 6 | "Spain" | | 7 | "Regent" | | 8 | "Soho" |
| | globalScore | 0.794 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 108 | | 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 | 1496 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 138 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 31.17 | | std | 21.45 | | cv | 0.688 | | sampleLengths | | 0 | 45 | | 1 | 2 | | 2 | 90 | | 3 | 49 | | 4 | 5 | | 5 | 3 | | 6 | 54 | | 7 | 60 | | 8 | 30 | | 9 | 2 | | 10 | 55 | | 11 | 12 | | 12 | 4 | | 13 | 9 | | 14 | 13 | | 15 | 32 | | 16 | 47 | | 17 | 52 | | 18 | 27 | | 19 | 6 | | 20 | 11 | | 21 | 10 | | 22 | 67 | | 23 | 52 | | 24 | 58 | | 25 | 34 | | 26 | 19 | | 27 | 7 | | 28 | 5 | | 29 | 43 | | 30 | 28 | | 31 | 9 | | 32 | 36 | | 33 | 44 | | 34 | 53 | | 35 | 3 | | 36 | 59 | | 37 | 49 | | 38 | 34 | | 39 | 22 | | 40 | 19 | | 41 | 14 | | 42 | 22 | | 43 | 39 | | 44 | 20 | | 45 | 58 | | 46 | 36 | | 47 | 48 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 128 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 228 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 138 | | ratio | 0.014 | | matches | | 0 | "She let her military precision dictate her stride—measured, rhythmic, relentless." | | 1 | "The lockbox at the station held her firearm; department policy dictated no guns on routine surveillance." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 668 | | adjectiveStacks | 1 | | stackExamples | | 0 | "ugly, sickly orange glow," |
| | adverbCount | 9 | | adverbRatio | 0.01347305389221557 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.010479041916167664 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 138 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 138 | | mean | 10.84 | | std | 6.31 | | cv | 0.582 | | sampleLengths | | 0 | 10 | | 1 | 8 | | 2 | 16 | | 3 | 11 | | 4 | 2 | | 5 | 7 | | 6 | 10 | | 7 | 3 | | 8 | 39 | | 9 | 20 | | 10 | 11 | | 11 | 9 | | 12 | 8 | | 13 | 10 | | 14 | 4 | | 15 | 18 | | 16 | 5 | | 17 | 3 | | 18 | 8 | | 19 | 12 | | 20 | 34 | | 21 | 12 | | 22 | 12 | | 23 | 11 | | 24 | 2 | | 25 | 11 | | 26 | 6 | | 27 | 6 | | 28 | 8 | | 29 | 12 | | 30 | 6 | | 31 | 4 | | 32 | 2 | | 33 | 8 | | 34 | 8 | | 35 | 10 | | 36 | 8 | | 37 | 21 | | 38 | 5 | | 39 | 7 | | 40 | 4 | | 41 | 9 | | 42 | 13 | | 43 | 20 | | 44 | 12 | | 45 | 11 | | 46 | 9 | | 47 | 16 | | 48 | 11 | | 49 | 6 |
| |
| 49.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.35507246376811596 | | totalSentences | 138 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 122 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 122 | | matches | | 0 | "She’d spent half the shift" | | 1 | "She let her military precision" | | 2 | "He sprinted with the chaotic" | | 3 | "She cleared the obstacle, landing" | | 4 | "She glanced at the worn" | | 5 | "She had to take him" | | 6 | "She burst onto the main" | | 7 | "His short curly dark brown" | | 8 | "His warm brown eyes widened" | | 9 | "He scrambled up a steep," | | 10 | "She grabbed onto exposed roots," | | 11 | "He threw himself over the" | | 12 | "She scaled the links rapidly," | | 13 | "His voice echoed, distorted and" | | 14 | "Her boots beat a relentless" | | 15 | "She unclipped her flashlight but" | | 16 | "She slid toward the bend" | | 17 | "It shifted locations every full" | | 18 | "Their faces remained obscured beneath" | | 19 | "He moved with practiced ease," |
| | ratio | 0.213 | |
| 5.08% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 111 | | totalSentences | 122 | | matches | | 0 | "Rain slashed against the London" | | 1 | "Harlow hammered her boots against" | | 2 | "Water whipped into her brown" | | 3 | "The pursuit had started an" | | 4 | "Harlow had staked out a" | | 5 | "The Raven's Nest." | | 6 | "She’d spent half the shift" | | 7 | "Harlow wiped the freezing rain" | | 8 | "She let her military precision" | | 9 | "Herrera lacked her discipline." | | 10 | "He sprinted with the chaotic" | | 11 | "Herrera vaulted a rusted dumpster" | | 12 | "A loose piece of metal" | | 13 | "Sodium streetlights bathed the brickwork" | | 14 | "Harlow leaped onto overturned wooden" | | 15 | "She cleared the obstacle, landing" | | 16 | "She glanced at the worn" | | 17 | "Backup wouldn't reach this part" | | 18 | "The storm had paralyzed the" | | 19 | "She had to take him" |
| | ratio | 0.91 | |
| 40.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 122 | | matches | | 0 | "Now on foot, the chase" |
| | ratio | 0.008 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 72 | | technicalSentenceCount | 4 | | matches | | 0 | "He sprinted with the chaotic energy of the hunted, his boots slipping and sliding over the treacherous cobblestones." | | 1 | "Surveillance that had shattered the moment Herrera made her in Soho." | | 2 | "Figures haggled over ancient manuscripts and jagged weapons that absorbed the unnatural light." | | 3 | "He moved with practiced ease, wiping the mud from his coat, tucking his medallion back beneath his collar." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |