| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.314 | | leniency | 0.629 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.81% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1615 | | 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) | |
| 81.42% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1615 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "echoed" | | 1 | "footsteps" | | 2 | "pristine" | | 3 | "flickered" | | 4 | "electric" |
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| 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 | 93 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 93 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 3 | | totalWords | 1628 | | ratio | 0.002 | | matches | | 0 | "Camden. Ask questions." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 1126 | | uniqueNames | 14 | | maxNameDensity | 0.89 | | worstName | "Farrow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Farrow" | | discoveredNames | | Tube | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 6 | | Camden | 2 | | Farrow | 10 | | South | 1 | | Kentish | 1 | | Town | 1 | | Edwardian | 1 | | Morris | 4 | | Hale | 3 | | Vincent | 1 | | Three | 5 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Camden" | | 3 | "Farrow" | | 4 | "Morris" | | 5 | "Hale" | | 6 | "Vincent" |
| | places | | 0 | "South" | | 1 | "Kentish" | | 2 | "Town" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 39.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like he'd been pulled from a dinne" | | 1 | "looked like he'd lain down for a nap and" | | 2 | "quite a scratch and wasn't quite a burn" | | 3 | "quite a burn" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1628 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 35.39 | | std | 25.64 | | cv | 0.724 | | sampleLengths | | 0 | 73 | | 1 | 58 | | 2 | 49 | | 3 | 62 | | 4 | 36 | | 5 | 66 | | 6 | 20 | | 7 | 71 | | 8 | 5 | | 9 | 15 | | 10 | 43 | | 11 | 3 | | 12 | 22 | | 13 | 6 | | 14 | 65 | | 15 | 84 | | 16 | 5 | | 17 | 14 | | 18 | 19 | | 19 | 15 | | 20 | 21 | | 21 | 67 | | 22 | 31 | | 23 | 14 | | 24 | 23 | | 25 | 82 | | 26 | 5 | | 27 | 1 | | 28 | 38 | | 29 | 20 | | 30 | 14 | | 31 | 52 | | 32 | 8 | | 33 | 91 | | 34 | 71 | | 35 | 31 | | 36 | 38 | | 37 | 2 | | 38 | 61 | | 39 | 38 | | 40 | 26 | | 41 | 48 | | 42 | 44 | | 43 | 14 | | 44 | 3 | | 45 | 54 |
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| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 93 | | matches | | 0 | "been pulled" | | 1 | "been trained " | | 2 | "been removed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 183 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 117 | | ratio | 0.077 | | matches | | 0 | "The air down here tasted of rust and old water, with something else underneath — something faintly metallic that sat wrong on the back of her tongue, like sucking on a copper coin." | | 1 | "\"You said the word 'anomalous.' I was in the car before you finished the sentence.\" She straightened and took in the platform — the old South Kentish Town station, closed since 1924, its walls still wearing fragments of Edwardian advertising beneath decades of grime." | | 2 | "Dark coat, dark trousers, expensive shoes — the kind with leather soles that would have clicked on a proper floor." | | 3 | "She studied the man's face — slack, grey, the eyes half-open and staring at the vaulted ceiling with an expression that might have been surprise or might have been nothing at all." | | 4 | "Quinn stood and took three slow steps backward, her eyes moving across the platform in a grid pattern the way she'd been trained — the way Morris had trained her, before." | | 5 | "Halfway between the body and the tunnel mouth, something caught the light — a faint scuffing on the tile, a mark that wasn't quite a scratch and wasn't quite a burn." | | 6 | "The fingertips were clean — too clean." | | 7 | "Near the tunnel mouth, behind a corroded pipe, she found it — a symbol scratched into the glaze, small enough to miss if you weren't looking." | | 8 | "Three feet away, another symbol — different, but with the same careful execution." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1121 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.032114183764495985 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006244424620874219 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 13.91 | | std | 11.15 | | cv | 0.802 | | sampleLengths | | 0 | 40 | | 1 | 33 | | 2 | 7 | | 3 | 21 | | 4 | 7 | | 5 | 23 | | 6 | 15 | | 7 | 24 | | 8 | 5 | | 9 | 5 | | 10 | 44 | | 11 | 15 | | 12 | 3 | | 13 | 14 | | 14 | 22 | | 15 | 12 | | 16 | 20 | | 17 | 11 | | 18 | 3 | | 19 | 2 | | 20 | 4 | | 21 | 14 | | 22 | 7 | | 23 | 13 | | 24 | 12 | | 25 | 32 | | 26 | 3 | | 27 | 12 | | 28 | 12 | | 29 | 5 | | 30 | 15 | | 31 | 27 | | 32 | 16 | | 33 | 3 | | 34 | 22 | | 35 | 6 | | 36 | 31 | | 37 | 11 | | 38 | 7 | | 39 | 1 | | 40 | 15 | | 41 | 18 | | 42 | 31 | | 43 | 7 | | 44 | 28 | | 45 | 5 | | 46 | 9 | | 47 | 5 | | 48 | 19 | | 49 | 2 |
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| 54.99% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.4017094017094017 | | totalSentences | 117 | | uniqueOpeners | 47 | |
| 40.65% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 82 | | matches | | 0 | "Somewhere deeper in the tunnel," |
| | ratio | 0.012 | |
| 78.54% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 82 | | matches | | 0 | "She checked her watch out" | | 1 | "He emerged from behind a" | | 2 | "She straightened and took in" | | 3 | "His arms were at his" | | 4 | "He looked like he'd lain" | | 5 | "She studied the man's face" | | 6 | "She leaned closer." | | 7 | "She tilted her head, studying" | | 8 | "She pulled a small flashlight" | | 9 | "She crouched again, bringing the" | | 10 | "He walked over, squatting beside" | | 11 | "It was a clean theory." | | 12 | "It accounted for the body," | | 13 | "He'd built a career on" | | 14 | "She studied Hale's hands, turning" | | 15 | "She checked the soles of" | | 16 | "She could see him rerunning" | | 17 | "he said, but there was" | | 18 | "She wasn't sure yet." | | 19 | "She stood and walked to" |
| | ratio | 0.354 | |
| 69.76% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 82 | | matches | | 0 | "The fluorescent work lights carved" | | 1 | "The air down here tasted" | | 2 | "She checked her watch out" | | 3 | "The worn leather band had" | | 4 | "He emerged from behind a" | | 5 | "She straightened and took in" | | 6 | "The tiled arches gave the" | | 7 | "Farrow led her along the" | | 8 | "The work lights had been" | | 9 | "A man, mid-thirties perhaps, lay" | | 10 | "His arms were at his" | | 11 | "He looked like he'd lain" | | 12 | "Farrow said, consulting his phone" | | 13 | "Quinn crouched beside the body," | | 14 | "She studied the man's face" | | 15 | "She leaned closer." | | 16 | "The pupils were fixed, but" | | 17 | "She tilted her head, studying" | | 18 | "Quinn stood and took three" | | 19 | "The dust on the tiles" |
| | ratio | 0.78 | |
| 60.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 82 | | matches | | 0 | "As though he had materialised" |
| | ratio | 0.012 | |
| 34.16% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 7 | | matches | | 0 | "The fluorescent work lights carved harsh white cones through the darkness of the abandoned Tube station, and Detective Harlow Quinn ducked beneath the police ta…" | | 1 | "Dark coat, dark trousers, expensive shoes — the kind with leather soles that would have clicked on a proper floor." | | 2 | "She studied the man's face — slack, grey, the eyes half-open and staring at the vaulted ceiling with an expression that might have been surprise or might have b…" | | 3 | "The mark was irregular, roughly hand-sized, and the tile beneath it had discoloured to a dull greenish-black, as if something corrosive had rested there and the…" | | 4 | "She could see him rerunning the scene in his head, rearranging the pieces." | | 5 | "But Morris had died in a room with no exits, no weapons, and no witnesses, and the case file sat in her desk drawer with a stamp that said CLOSED and a truth un…" | | 6 | "Somewhere deeper in the tunnel, water dripped in a rhythm that sounded almost intentional." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |