| 66.67% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 2 | | adverbTags | | 0 | "His accent curled around [around]" | | 1 | "a single phrase underlined twice [twice]" |
| | dialogueSentences | 30 | | tagDensity | 0.267 | | leniency | 0.533 | | rawRatio | 0.25 | | effectiveRatio | 0.133 | |
| 91.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1222 | | 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) | |
| 67.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1222 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "flicked" | | 1 | "scanning" | | 2 | "standard" | | 3 | "glistening" | | 4 | "pulse" | | 5 | "weight" | | 6 | "echoing" | | 7 | "pulsed" |
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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 | 1 | | narrationSentences | 123 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 123 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 145 | | 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 | 6 | | markdownWords | 31 | | totalWords | 1204 | | ratio | 0.026 | | matches | | 0 | "Employees Only" | | 1 | "Underground black market. Supernatural wares. Cops don’t go there and come back right in the head." | | 2 | "really" | | 3 | "key" | | 4 | "\"It was never a crime scene. It was a ritual.\"" | | 5 | "alive" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 977 | | uniqueNames | 14 | | maxNameDensity | 0.92 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Oxford | 1 | | Street | 1 | | Harlow | 1 | | Quinn | 9 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Morris | 5 | | Tube | 1 | | Veil | 2 | | Market | 2 | | Spanish | 1 | | London | 1 | | Herrera | 5 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Market" | | 4 | "Spanish" | | 5 | "Herrera" |
| | places | | 0 | "Oxford" | | 1 | "Street" | | 2 | "Soho" | | 3 | "Raven" | | 4 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | 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 | 1204 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 145 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 74 | | mean | 16.27 | | std | 16.1 | | cv | 0.99 | | sampleLengths | | 0 | 62 | | 1 | 16 | | 2 | 11 | | 3 | 43 | | 4 | 26 | | 5 | 12 | | 6 | 47 | | 7 | 5 | | 8 | 2 | | 9 | 2 | | 10 | 59 | | 11 | 7 | | 12 | 8 | | 13 | 15 | | 14 | 3 | | 15 | 53 | | 16 | 2 | | 17 | 2 | | 18 | 10 | | 19 | 54 | | 20 | 3 | | 21 | 28 | | 22 | 4 | | 23 | 6 | | 24 | 56 | | 25 | 27 | | 26 | 5 | | 27 | 30 | | 28 | 4 | | 29 | 13 | | 30 | 22 | | 31 | 6 | | 32 | 3 | | 33 | 6 | | 34 | 8 | | 35 | 32 | | 36 | 4 | | 37 | 10 | | 38 | 4 | | 39 | 29 | | 40 | 7 | | 41 | 23 | | 42 | 3 | | 43 | 16 | | 44 | 5 | | 45 | 6 | | 46 | 4 | | 47 | 29 | | 48 | 3 | | 49 | 8 |
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| 99.56% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 123 | | matches | | 0 | "been played" | | 1 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 185 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 15 | | totalSentences | 145 | | ratio | 0.103 | | matches | | 0 | "Detective Harlow Quinn moved through it like a blade through wet paper—shoulders low, coat tight to her frame, breath steady despite the sprint." | | 1 | "She recognized the route—knew it like the scar tissue around her partner’s unsolved file." | | 2 | "The suspect—hood up, face shadowed—cut through the middle, leapt over a trash bin, and vanished behind a graffiti-tagged door marked *Employees Only*." | | 3 | "The air below smelled of damp concrete and something older—incense, maybe, or decay masked by spice." | | 4 | "A faint hum buzzed beneath her feet—subway trains, maybe, or generators." | | 5 | "Dozens of stalls crammed a cavernous space—once a disused Tube station, by the tiled arches and rusted tracks now buried under foot-traffic." | | 6 | "A stall sold bottled smoke—labelled in a script she didn’t recognize." | | 7 | "He pressed a silver coin into her palm—tarnished, oddly shaped." | | 8 | "His eyes—warm brown, sharp with urgency—locked onto hers." | | 9 | "\"Then you *really* don’t want to do this.\" His accent curled around the words—Spanish, trained now by years in London." | | 10 | "His scar—a pale ridge along his left forearm—glistened under the light as he shifted his weight." | | 11 | "The market buzzed around them—incantations murmured in dialects not from this world, the reek of burnt sage and copper-rich blood." | | 12 | "Somewhere, a bell chimed—three slow tones." | | 13 | "The walls pulsed with symbols now—carved, painted, *alive*." | | 14 | "Quinn touched the watch on her wrist—Morris’s old field chronometer, the one she’d found in his locker, stopped at 3:17 a.m." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1005 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.026865671641791045 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0029850746268656717 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 145 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 145 | | mean | 8.3 | | std | 6.28 | | cv | 0.757 | | sampleLengths | | 0 | 25 | | 1 | 23 | | 2 | 14 | | 3 | 16 | | 4 | 11 | | 5 | 4 | | 6 | 13 | | 7 | 22 | | 8 | 4 | | 9 | 14 | | 10 | 4 | | 11 | 4 | | 12 | 4 | | 13 | 12 | | 14 | 14 | | 15 | 22 | | 16 | 3 | | 17 | 8 | | 18 | 5 | | 19 | 2 | | 20 | 2 | | 21 | 9 | | 22 | 16 | | 23 | 5 | | 24 | 16 | | 25 | 13 | | 26 | 4 | | 27 | 3 | | 28 | 8 | | 29 | 6 | | 30 | 9 | | 31 | 3 | | 32 | 12 | | 33 | 6 | | 34 | 11 | | 35 | 24 | | 36 | 2 | | 37 | 1 | | 38 | 1 | | 39 | 10 | | 40 | 9 | | 41 | 4 | | 42 | 22 | | 43 | 6 | | 44 | 13 | | 45 | 3 | | 46 | 4 | | 47 | 8 | | 48 | 3 | | 49 | 2 |
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| 68.51% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.4482758620689655 | | totalSentences | 145 | | uniqueOpeners | 65 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 107 | | matches | | 0 | "Just bolted left, down a" | | 1 | "Then she saw him stop." | | 2 | "Somewhere, a bell chimed—three slow" | | 3 | "Still see the spiral symbol" |
| | ratio | 0.037 | |
| 77.94% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 107 | | matches | | 0 | "Her worn leather watch dug" | | 1 | "She pushed off, gaining." | | 2 | "She recognized the route—knew it" | | 3 | "It twisted toward Soho." | | 4 | "She wrenched the door open," | | 5 | "She flicked on her torch." | | 6 | "She’d seen it before." | | 7 | "Her fingers tightened around the" | | 8 | "Her other hand brushed the" | | 9 | "She started down." | | 10 | "She flattened against the tunnel" | | 11 | "She edged forward, keeping low," | | 12 | "Her suspect pushed through a" | | 13 | "He approached a woman in" | | 14 | "She handed him a small" | | 15 | "He pressed a silver coin" | | 16 | "She could radio for backup." | | 17 | "She stepped forward." | | 18 | "She spun, gun half-drawn, before" | | 19 | "His eyes—warm brown, sharp with" |
| | ratio | 0.355 | |
| 95.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 107 | | matches | | 0 | "Rain sluiced down Oxford Street" | | 1 | "Detective Harlow Quinn moved through" | | 2 | "Her worn leather watch dug" | | 3 | "Quinn barked, voice cutting through" | | 4 | "The figure didn’t turn." | | 5 | "Quinn followed, boots slipping once" | | 6 | "She pushed off, gaining." | | 7 | "She recognized the route—knew it" | | 8 | "This path wasn’t random." | | 9 | "It twisted toward Soho." | | 10 | "The alley opened into a" | | 11 | "The suspect—hood up, face shadowed—cut" | | 12 | "Quinn didn’t hesitate." | | 13 | "She wrenched the door open," | | 14 | "Stairs spiraled down into darkness." | | 15 | "The air below smelled of" | | 16 | "She flicked on her torch." | | 17 | "The beam cut through the" | | 18 | "She’d seen it before." | | 19 | "Her fingers tightened around the" |
| | ratio | 0.729 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 107 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn barked, voice cutting through the drum of rain" |
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| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn barked (bark)" | | 1 | "Quinn muttered (mutter)" |
| | dialogueSentences | 30 | | tagDensity | 0.133 | | leniency | 0.267 | | rawRatio | 0.5 | | effectiveRatio | 0.133 | |