| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 26 | | tagDensity | 0.192 | | leniency | 0.385 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1375 | | 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) | |
| 34.55% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1375 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "measured" | | 1 | "glint" | | 2 | "flickered" | | 3 | "gloom" | | 4 | "weight" | | 5 | "rhythmic" | | 6 | "mechanical" | | 7 | "footsteps" | | 8 | "echoed" | | 9 | "glinting" | | 10 | "scanned" | | 11 | "stomach" | | 12 | "shattered" | | 13 | "maw" | | 14 | "scanning" |
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| 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 | 0 | | narrationSentences | 145 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 145 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 167 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 29 | | markdownWords | 37 | | totalWords | 1359 | | ratio | 0.027 | | matches | | 0 | "The Raven’s Nest" | | 1 | "clinked" | | 2 | "That’s new." | | 3 | "wrong" | | 4 | "\"Quinn, where the fuck are you?\"" | | 5 | "thump" | | 6 | "God" | | 7 | "twitched" | | 8 | "knowing" | | 9 | "was" | | 10 | "detective" | | 11 | "soulglass" | | 12 | "empty" | | 13 | "people" | | 14 | "pig" | | 15 | "unfolded" | | 16 | "teeth" | | 17 | "inhaled" | | 18 | "many" | | 19 | "fuck" | | 20 | "lunged" | | 21 | "dead" | | 22 | "there" | | 23 | "Now" | | 24 | "shifted" | | 25 | "breathed" | | 26 | "Harlow" | | 27 | "chittered" | | 28 | "wrong" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1212 | | uniqueNames | 14 | | maxNameDensity | 1.49 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Quinn | 1 | | Greek | 1 | | Street | 1 | | Raven | 1 | | Morris | 3 | | London | 1 | | Camden | 1 | | Occult | 1 | | Crimes | 1 | | Veil | 1 | | Market | 1 | | Herrera | 1 | | Tomás | 12 | | Harlow | 18 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Camden" | | 3 | "Market" | | 4 | "Herrera" | | 5 | "Tomás" | | 6 | "Harlow" |
| | places | | 0 | "Greek" | | 1 | "Street" | | 2 | "Raven" | | 3 | "London" | | 4 | "Occult" |
| | globalScore | 0.757 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 85 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like preserved tongues" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.736 | | wordCount | 1359 | | matches | | 0 | "not out of respect, but the way water parts around a stone" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 167 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 69 | | mean | 19.7 | | std | 17.23 | | cv | 0.875 | | sampleLengths | | 0 | 75 | | 1 | 62 | | 2 | 20 | | 3 | 36 | | 4 | 49 | | 5 | 3 | | 6 | 42 | | 7 | 33 | | 8 | 12 | | 9 | 15 | | 10 | 67 | | 11 | 30 | | 12 | 6 | | 13 | 5 | | 14 | 66 | | 15 | 3 | | 16 | 30 | | 17 | 47 | | 18 | 28 | | 19 | 6 | | 20 | 36 | | 21 | 15 | | 22 | 7 | | 23 | 13 | | 24 | 12 | | 25 | 14 | | 26 | 27 | | 27 | 27 | | 28 | 26 | | 29 | 10 | | 30 | 16 | | 31 | 44 | | 32 | 5 | | 33 | 40 | | 34 | 3 | | 35 | 8 | | 36 | 14 | | 37 | 17 | | 38 | 3 | | 39 | 6 | | 40 | 37 | | 41 | 2 | | 42 | 22 | | 43 | 25 | | 44 | 11 | | 45 | 14 | | 46 | 29 | | 47 | 23 | | 48 | 5 | | 49 | 4 |
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| 95.58% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 145 | | matches | | 0 | "was plastered" | | 1 | "was gone" | | 2 | "was gone" | | 3 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 225 | | matches | | 0 | "was descending" | | 1 | "was fighting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 167 | | ratio | 0.054 | | matches | | 0 | "The suspect—tall, lanky, moving like a man who knew these streets better than his own reflection—ducked left, then right, weaving through the late-night stragglers with the ease of a rat in the walls." | | 1 | "A shout rose behind her—uniforms, slow on the uptake, still blundering through the alleyways." | | 2 | "Boots scuffed against metal—he was descending." | | 3 | "Her torchlight caught symbols carved into the brickwork—warding marks, if the files she’d “borrowed” from Occult Crimes were anything to go by." | | 4 | "A child—if it *was* a child—with eyes like polished coal pointed and giggled." | | 5 | "The scream came again—closer this time, from a curtained-off alcove near the back." | | 6 | "Tomás dragged her behind an overturned cart, its contents—jars of eyeballs, a hand with too many fingers—spilling across the cobblestones." | | 7 | "But the satchel—*there*." | | 8 | "She snatched the satchel, turned—" |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 673 | | adjectiveStacks | 1 | | stackExamples | | 0 | "suspect—tall, lanky, moving like" |
| | adverbCount | 16 | | adverbRatio | 0.0237741456166419 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004457652303120356 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 167 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 167 | | mean | 8.14 | | std | 5.89 | | cv | 0.723 | | sampleLengths | | 0 | 16 | | 1 | 4 | | 2 | 22 | | 3 | 33 | | 4 | 11 | | 5 | 26 | | 6 | 8 | | 7 | 7 | | 8 | 10 | | 9 | 14 | | 10 | 3 | | 11 | 3 | | 12 | 16 | | 13 | 15 | | 14 | 3 | | 15 | 2 | | 16 | 14 | | 17 | 4 | | 18 | 9 | | 19 | 8 | | 20 | 14 | | 21 | 3 | | 22 | 15 | | 23 | 21 | | 24 | 6 | | 25 | 10 | | 26 | 7 | | 27 | 2 | | 28 | 3 | | 29 | 11 | | 30 | 6 | | 31 | 6 | | 32 | 7 | | 33 | 8 | | 34 | 7 | | 35 | 3 | | 36 | 23 | | 37 | 12 | | 38 | 22 | | 39 | 5 | | 40 | 14 | | 41 | 6 | | 42 | 5 | | 43 | 6 | | 44 | 5 | | 45 | 17 | | 46 | 10 | | 47 | 7 | | 48 | 20 | | 49 | 12 |
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| 42.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.2994011976047904 | | totalSentences | 167 | | uniqueOpeners | 50 | |
| 74.07% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 135 | | matches | | 0 | "Then he vanished." | | 1 | "Just the promise of whatever" | | 2 | "Only the satchel in her" |
| | ratio | 0.022 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 135 | | matches | | 0 | "Her breath came steady, measured," | | 1 | "She’d been tailing him since" | | 2 | "She ignored them." | | 3 | "His coat flapped open, revealing" | | 4 | "He bolted across the road," | | 5 | "She vaulted the bonnet, landed" | | 6 | "Her torch flickered to life," | | 7 | "She yanked it out, let" | | 8 | "Her torchlight caught symbols carved" | | 9 | "Her boots hit solid ground." | | 10 | "She raised the torch higher." | | 11 | "She stepped forward." | | 12 | "They feared something else." | | 13 | "His curly hair was plastered" | | 14 | "She knocked his hand off." | | 15 | "His jaw tightened." | | 16 | "She scanned the stalls again" | | 17 | "Her voice dropped" | | 18 | "He grabbed her arm, pulled" | | 19 | "She shoved him aside." |
| | ratio | 0.222 | |
| 22.96% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 118 | | totalSentences | 135 | | matches | | 0 | "Harlow Quinn didn’t flinch." | | 1 | "Her breath came steady, measured," | | 2 | "The suspect—tall, lanky, moving like" | | 3 | "She’d been tailing him since" | | 4 | "Harlow had seen that kind" | | 5 | "The kind of thing that" | | 6 | "A shout rose behind her—uniforms," | | 7 | "She ignored them." | | 8 | "This was hers." | | 9 | "The suspect glanced back, eyes" | | 10 | "His coat flapped open, revealing" | | 11 | "Harlow’s fingers twitched." | | 12 | "He bolted across the road," | | 13 | "Harlow didn’t break stride." | | 14 | "She vaulted the bonnet, landed" | | 15 | "The suspect was fast, but" | | 16 | "Harlow skidded to a halt" | | 17 | "A wrought-iron grate lay upturned," | | 18 | "Boots scuffed against metal—he was" | | 19 | "Her torch flickered to life," |
| | ratio | 0.874 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 135 | | matches | (empty) | | ratio | 0 | |
| 49.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 6 | | matches | | 0 | "The suspect—tall, lanky, moving like a man who knew these streets better than his own reflection—ducked left, then right, weaving through the late-night straggl…" | | 1 | "Silly bastard had thought he could slip out the back with a satchel full of something that *clinked* like glass and hummed like a live wire." | | 2 | "The tunnel stretched ahead, lit by flickering gas lamps that shouldn’t have been there." | | 3 | "Bottles of liquid that shifted colours like oil on water." | | 4 | "A man with a face like melted wax blocked her path, hissing something in a language that made her teeth ache." | | 5 | "The spirit writhed, a mass of smoke and snapping jaws, devouring anything that moved too slow." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |