| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1644 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "gently" | | 2 | "slowly" |
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| 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) | |
| 60.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1644 | | totalAiIsms | 13 | | found | | 0 | | | 1 | | word | "carried the weight" | | count | 1 |
| | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | |
| | highlights | | 0 | "flickered" | | 1 | "carried the weight" | | 2 | "echoed" | | 3 | "standard" | | 4 | "traced" | | 5 | "weight" | | 6 | "mechanical" | | 7 | "resolve" | | 8 | "charged" | | 9 | "vibrated" | | 10 | "pristine" | | 11 | "pulse" |
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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 | 65 | | matches | (empty) | |
| 10.99% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 3 | | narrationSentences | 65 | | filterMatches | | | hedgeMatches | | 0 | "began to" | | 1 | "try to" | | 2 | "appeared to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 74 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 81 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1632 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 1229 | | uniqueNames | 6 | | maxNameDensity | 0.81 | | worstName | "Wilkins" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Wilkins" | | discoveredNames | | Quinn | 9 | | Tube | 1 | | Camden | 1 | | Tom | 1 | | Wilkins | 10 | | Morris | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Camden" | | 2 | "Tom" | | 3 | "Wilkins" | | 4 | "Morris" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 1 | | matches | | 0 | "as though responding to something beyond the torch beam" |
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| 77.45% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.225 | | wordCount | 1632 | | matches | | 0 | "not toward true north but toward the far alcove" | | 1 | "not for convenience but for its hidden alignments, locations" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 74 | | matches | (empty) | |
| 64.02% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 19 | | mean | 85.89 | | std | 32.13 | | cv | 0.374 | | sampleLengths | | 0 | 131 | | 1 | 89 | | 2 | 112 | | 3 | 63 | | 4 | 70 | | 5 | 43 | | 6 | 108 | | 7 | 31 | | 8 | 117 | | 9 | 51 | | 10 | 34 | | 11 | 86 | | 12 | 88 | | 13 | 56 | | 14 | 132 | | 15 | 91 | | 16 | 137 | | 17 | 95 | | 18 | 98 |
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| 72.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 65 | | matches | | 0 | "been lowered" | | 1 | "been opened" | | 2 | "been sealed" | | 3 | "been cleared" | | 4 | "was pulled" | | 5 | "been chosen" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 198 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 4 | | flaggedSentences | 12 | | totalSentences | 74 | | ratio | 0.162 | | matches | | 0 | "The worn leather watch on her left wrist caught a gleam of light as she checked the time again—nearly one in the morning, the sort of hour when the ordinary truths of a crime scene began to fray at the edges." | | 1 | "She crouched, the concrete cold through her trousers, and noted the faint swirl of dust around the shoulders—almost as though something had brushed the platform after the body settled." | | 2 | "The face carried faint etchings—curved lines that crossed in protective patterns rather than standard cardinal marks." | | 3 | "“Probably nothing. Some old souvenir he kept for luck or navigation down here. The light’s bad; the needle’s likely borked from the damp.”" | | 4 | "The beam of her own torch revealed a faint seam in the concrete wall—no wider than a credit card, yet straight and deliberate, running from floor to the height of her shoulders before disappearing behind a rusted conduit." | | 5 | "A bone token, smooth and carved with shallow spirals, rested half beneath the victim’s other hand; she nudged it free with a pen." | | 6 | "“You’re reading too much into a broken gadget and a bit of old bone, Detective. The lab will sort the wound; most of these underground jobs end the same—territory, debt, or a double-cross over inventory that doesn’t match the manifest. No need to chase shadows when the scene already tells the plain story.”" | | 7 | "The faint ozone scent that rose from the seam wasn’t from the railway lines; it hung differently, like charged air after a storm that never broke." | | 8 | "The edges weren’t straight cuts but slightly curved, spaced in a pattern no standard blade left without a serrated edge—and there was no serrated edge present in the dust or on the victim’s clothing." | | 9 | "Someone— or something—had opened the barrier only from this side, then left it ajar just far enough for the body to be carried through before it was pulled shut again." | | 10 | "Three years ago, her partner Morris had described a similar mismatch in another sealed space—wounds without weapons, entry without force—and the case had closed itself around an explanation nobody could prove." | | 11 | "Whatever had taken place here had used the station’s forgotten architecture the way a lockpick uses a tumbler—quiet, precise, and invisible to anyone looking only for blood and blades." |
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| 99.66% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1238 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 50 | | adverbRatio | 0.04038772213247173 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.009693053311793215 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 74 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 74 | | mean | 22.05 | | std | 13.87 | | cv | 0.629 | | sampleLengths | | 0 | 34 | | 1 | 27 | | 2 | 29 | | 3 | 41 | | 4 | 21 | | 5 | 23 | | 6 | 10 | | 7 | 35 | | 8 | 8 | | 9 | 21 | | 10 | 31 | | 11 | 19 | | 12 | 29 | | 13 | 4 | | 14 | 13 | | 15 | 50 | | 16 | 17 | | 17 | 16 | | 18 | 15 | | 19 | 4 | | 20 | 18 | | 21 | 5 | | 22 | 38 | | 23 | 25 | | 24 | 32 | | 25 | 16 | | 26 | 7 | | 27 | 28 | | 28 | 8 | | 29 | 23 | | 30 | 16 | | 31 | 18 | | 32 | 38 | | 33 | 18 | | 34 | 7 | | 35 | 20 | | 36 | 5 | | 37 | 46 | | 38 | 9 | | 39 | 25 | | 40 | 10 | | 41 | 18 | | 42 | 23 | | 43 | 5 | | 44 | 14 | | 45 | 16 | | 46 | 7 | | 47 | 81 | | 48 | 3 | | 49 | 53 |
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| 59.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.3783783783783784 | | totalSentences | 74 | | uniqueOpeners | 28 | |
| 52.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 63 | | matches | | 0 | "Instead she stored each mismatch:" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 63 | | matches | | 0 | "he said, voice low enough" | | 1 | "It lay near the platform" | | 2 | "She crouched, the concrete cold" | | 3 | "She stood and walked the" | | 4 | "She let the explanation hang," | | 5 | "She lifted it clear, turning" | | 6 | "She walked toward the alcove" | | 7 | "She traced one finger along" | | 8 | "She turned back to Wilkins." | | 9 | "It held its bearing on" | | 10 | "It fitted her palm like" | | 11 | "She stepped back to the" | | 12 | "She walked the platform to" | | 13 | "She returned to Wilkins and" | | 14 | "She moved toward the stairs" |
| | ratio | 0.238 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 63 | | matches | | 0 | "Harlow Quinn paused at the" | | 1 | "The emergency lights the forensics" | | 2 | "The worn leather watch on" | | 3 | "DS Tom Wilkins waited at" | | 4 | "The air down here tasted" | | 5 | "he said, voice low enough" | | 6 | "Quinn nodded once and crossed" | | 7 | "It lay near the platform" | | 8 | "The single gash across the" | | 9 | "She crouched, the concrete cold" | | 10 | "Wilkins crouched too, torchlight catching" | | 11 | "Quinn’s brown eyes tracked from" | | 12 | "The heavy iron bars above" | | 13 | "She stood and walked the" | | 14 | "The barrier held firm." | | 15 | "Wilkins shrugged, rising with her." | | 16 | "She let the explanation hang," | | 17 | "The face carried faint etchings—curved" | | 18 | "She lifted it clear, turning" | | 19 | "The casing felt older than" |
| | ratio | 0.857 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 6 | | matches | | 0 | "Harlow Quinn paused at the mouth of the rusted stairwell that dropped into the abandoned Tube station beneath Camden, letting the damp night air settle against …" | | 1 | "She crouched, the concrete cold through her trousers, and noted the faint swirl of dust around the shoulders—almost as though something had brushed the platform…" | | 2 | "It held its bearing on the seam, trembling once as though responding to something beyond the torch beam." | | 3 | "The skin around each mark showed the cleanest cauterization she’d seen outside controlled burns, as though the tissue had been sealed the instant the strike lan…" | | 4 | "Wilkins remained by the body, logging the time of death window on his pad, insisting the simplest version would hold." | | 5 | "The station itself had been chosen not for convenience but for its hidden alignments, locations that shifted yet always returned to points where normal barriers…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, voice low enough that it echoed anyway" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.231 | | leniency | 0.462 | | rawRatio | 0 | | effectiveRatio | 0 | |