| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.76% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 954 | | totalAiIsmAdverbs | 1 | | found | | 0 | | adverb | "reluctantly" | | count | 1 |
|
| | 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) | |
| 26.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 954 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "methodical" | | 1 | "tension" | | 2 | "flicked" | | 3 | "flickered" | | 4 | "tinged" | | 5 | "echo" | | 6 | "silence" | | 7 | "whisper" | | 8 | "chill" | | 9 | "pulsed" | | 10 | "traced" | | 11 | "rhythmic" |
| |
| 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 | 151 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 151 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 169 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 9 | | markdownWords | 23 | | totalWords | 932 | | ratio | 0.025 | | matches | | 0 | "felt" | | 1 | "FOR LEASE" | | 2 | "Veil Market rules" | | 3 | "do something else" | | 4 | "You’re close" | | 5 | "But you don’t see the whole board." | | 6 | "Clocks." | | 7 | "Detective Reeves" | | 8 | "Suspect Suicide" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 75.47% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 805 | | uniqueNames | 21 | | maxNameDensity | 1.49 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Audi | 1 | | Wardour | 1 | | Street | 3 | | Greek | 2 | | Soho | 1 | | Harlow | 12 | | Carnaby | 1 | | Broadwick | 1 | | Italian | 1 | | Market | 4 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Veil | 4 | | Ghosts | 1 | | Three | 1 | | Morris | 1 | | Stolen | 1 | | Tomás | 4 | | Latin | 1 | | Glock | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Market" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Morris" | | 6 | "Tomás" |
| | places | | 0 | "Wardour" | | 1 | "Street" | | 2 | "Greek" | | 3 | "Soho" | | 4 | "Carnaby" | | 5 | "Broadwick" | | 6 | "Veil" |
| | globalScore | 0.755 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | 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 | 932 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 169 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 16.64 | | std | 14.14 | | cv | 0.85 | | sampleLengths | | 0 | 67 | | 1 | 45 | | 2 | 47 | | 3 | 3 | | 4 | 55 | | 5 | 25 | | 6 | 24 | | 7 | 1 | | 8 | 13 | | 9 | 30 | | 10 | 2 | | 11 | 22 | | 12 | 24 | | 13 | 18 | | 14 | 2 | | 15 | 6 | | 16 | 18 | | 17 | 3 | | 18 | 22 | | 19 | 3 | | 20 | 33 | | 21 | 7 | | 22 | 35 | | 23 | 5 | | 24 | 23 | | 25 | 7 | | 26 | 6 | | 27 | 3 | | 28 | 25 | | 29 | 22 | | 30 | 3 | | 31 | 6 | | 32 | 7 | | 33 | 15 | | 34 | 18 | | 35 | 14 | | 36 | 15 | | 37 | 10 | | 38 | 34 | | 39 | 32 | | 40 | 19 | | 41 | 14 | | 42 | 2 | | 43 | 14 | | 44 | 2 | | 45 | 25 | | 46 | 7 | | 47 | 4 | | 48 | 18 | | 49 | 20 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 151 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 164 | | matches | | 0 | "was waking" | | 1 | "was sealing" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 23 | | semicolonCount | 1 | | flaggedSentences | 20 | | totalSentences | 169 | | ratio | 0.118 | | matches | | 0 | "Harlow didn’t slow, just palmed the worn leather of her watch, checked the time—23:17—before throttling the wheel of her old Audi through the slick S-bend of Wardour Street." | | 1 | "Her headlights caught a flash of movement—dark coat, hunched shoulders—hurrying down a side alley." | | 2 | "One pretended not to see the chase; another laughed into a phone, filming." | | 3 | "The suspect ducked into an alcove—boarded-up Italian restaurant, glass doors taped with *FOR LEASE*." | | 4 | "Then—sound." | | 5 | "Not just damp—something else." | | 6 | "Arced brickwork, graffiti tags glowing faintly in bioluminescent paints—*Veil Market rules*: No iron." | | 7 | "Then—a whisper." | | 8 | "Then, last week—Morris in the precinct morgue." | | 9 | "He tugged the medallion—once, slow." | | 10 | "Somewhere ahead, music pulsed—slow, hypnotic." | | 11 | "Walls pulsed with sigils—Latin, Greek reversed, a few she didn’t recognise." | | 12 | "Then—sound." | | 13 | "And on it—objects." | | 14 | "Harlow drew her firearm—a Glock, modern alloy, not iron—not silver." | | 15 | "Smoke billowed—thick, green, acrid." | | 16 | "When the cloud cleared—" | | 17 | "A distant sound—stone grinding, air locking." | | 18 | "Fingers brushed it—cold as ice." | | 19 | "Close enough to smell—copper pennies and wintergreen." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 503 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.033797216699801194 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.003976143141153081 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 169 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 169 | | mean | 5.51 | | std | 4.11 | | cv | 0.745 | | sampleLengths | | 0 | 5 | | 1 | 28 | | 2 | 15 | | 3 | 3 | | 4 | 16 | | 5 | 6 | | 6 | 14 | | 7 | 7 | | 8 | 5 | | 9 | 13 | | 10 | 14 | | 11 | 6 | | 12 | 19 | | 13 | 2 | | 14 | 6 | | 15 | 3 | | 16 | 10 | | 17 | 7 | | 18 | 6 | | 19 | 14 | | 20 | 13 | | 21 | 5 | | 22 | 10 | | 23 | 10 | | 24 | 5 | | 25 | 14 | | 26 | 7 | | 27 | 3 | | 28 | 1 | | 29 | 1 | | 30 | 1 | | 31 | 4 | | 32 | 3 | | 33 | 4 | | 34 | 4 | | 35 | 10 | | 36 | 6 | | 37 | 10 | | 38 | 2 | | 39 | 3 | | 40 | 4 | | 41 | 1 | | 42 | 11 | | 43 | 3 | | 44 | 5 | | 45 | 13 | | 46 | 2 | | 47 | 2 | | 48 | 2 | | 49 | 6 |
| |
| 74.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.46745562130177515 | | totalSentences | 169 | | uniqueOpeners | 79 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 116 | | matches | | 0 | "Then, last week—Morris in the" | | 1 | "Instead, he tilted his head," | | 2 | "Somewhere ahead, music pulsed—slow, hypnotic." | | 3 | "Then, reluctantly, stepped aside." | | 4 | "Somewhere ahead, a table set" |
| | ratio | 0.043 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 116 | | matches | | 0 | "She didn’t hesitate." | | 1 | "She didn’t need the noise." | | 2 | "She *felt* the tension in" | | 3 | "Her headlights caught a flash" | | 4 | "She flicked the main beam" | | 5 | "Her shoes hit the pavement" | | 6 | "She cut through the crowd," | | 7 | "She hammered her fist against" | | 8 | "She swallowed bile." | | 9 | "He exhaled, slow." | | 10 | "She didn’t blink." | | 11 | "*You’re close*, he’d mouthed." | | 12 | "He tugged the medallion—once, slow." | | 13 | "She lunged forward." | | 14 | "He caught her wrist, firm." | | 15 | "She didn’t wait to hear" | | 16 | "She aimed centre mass." | | 17 | "They burst into flame." |
| | ratio | 0.155 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 116 | | matches | | 0 | "The sirens died behind her." | | 1 | "Harlow didn’t slow, just palmed" | | 2 | "The suspect’s tail-lights vanished around" | | 3 | "She didn’t hesitate." | | 4 | "Tyres screamed a protest, then" | | 5 | "The dispatcher’s voice was calm," | | 6 | "Harlow reached over and thumbed" | | 7 | "She didn’t need the noise." | | 8 | "She *felt* the tension in" | | 9 | "Her headlights caught a flash" | | 10 | "She flicked the main beam" | | 11 | "That was enough." | | 12 | "Harlow killed the engine two" | | 13 | "Her shoes hit the pavement" | | 14 | "The suspect was fast, weaving" | | 15 | "London’s night eye turned away." | | 16 | "She cut through the crowd," | | 17 | "The wine hit the ground," | | 18 | "Harlow didn’t pause to apologise." | | 19 | "The suspect ducked into an" |
| | ratio | 0.707 | |
| 43.10% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 116 | | matches | | 0 | "*But you don’t see the" |
| | ratio | 0.009 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | |
| 59.09% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "she demanded (demand)" | | 1 | "she snapped (snap)" |
| | dialogueSentences | 22 | | tagDensity | 0.227 | | leniency | 0.455 | | rawRatio | 0.4 | | effectiveRatio | 0.182 | |