| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn said quietly [quietly]" |
| | dialogueSentences | 26 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.077 | | effectiveRatio | 0.077 | |
| 88.58% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1314 | | totalAiIsmAdverbs | 3 | | found | | 0 | | adverb | "deliberately" | | count | 1 |
| | 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) | |
| 77.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1314 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "etched" | | 3 | "ceaseless" | | 4 | "magnetic" | | 5 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 88 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 88 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 100 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 62 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 5 | | totalWords | 1325 | | ratio | 0.004 | | matches | | 0 | "Camden" | | 1 | "clear" | | 2 | "missing presumed dead" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1070 | | uniqueNames | 12 | | maxNameDensity | 0.84 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 9 | | Tube | 1 | | Transport | 1 | | London | 2 | | Detective | 1 | | Sergeant | 1 | | Reyes | 6 | | Forty | 1 | | Underground | 1 | | Camden | 2 | | Deptford | 1 | | Morris | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Sergeant" | | 2 | "Reyes" | | 3 | "Forty" | | 4 | "Morris" |
| | places | | 0 | "London" | | 1 | "Underground" | | 2 | "Deptford" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 1 | | matches | | |
| 49.06% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.509 | | wordCount | 1325 | | matches | | 0 | "not confirmed but the uniforms found a wallet, John Doe until we run it" | | 1 | "not fear exactly, but recognition, the body's memory outrunning the mind's" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 100 | | matches | | 0 | "afford that refusal" | | 1 | "made that mistake" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 37.86 | | std | 28.29 | | cv | 0.747 | | sampleLengths | | 0 | 58 | | 1 | 24 | | 2 | 47 | | 3 | 9 | | 4 | 60 | | 5 | 78 | | 6 | 6 | | 7 | 48 | | 8 | 60 | | 9 | 8 | | 10 | 3 | | 11 | 3 | | 12 | 44 | | 13 | 52 | | 14 | 7 | | 15 | 42 | | 16 | 4 | | 17 | 104 | | 18 | 6 | | 19 | 94 | | 20 | 46 | | 21 | 11 | | 22 | 5 | | 23 | 56 | | 24 | 69 | | 25 | 24 | | 26 | 90 | | 27 | 13 | | 28 | 62 | | 29 | 9 | | 30 | 54 | | 31 | 34 | | 32 | 37 | | 33 | 33 | | 34 | 25 |
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| 89.31% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 88 | | matches | | 0 | "was crouched" | | 1 | "been built" | | 2 | "was etched" | | 3 | "was surprised" |
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| 50.19% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 178 | | matches | | 0 | "was looking" | | 1 | "was telling" | | 2 | "was spinning" | | 3 | "was beginning" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 1 | | flaggedSentences | 12 | | totalSentences | 100 | | ratio | 0.12 | | matches | | 0 | "Not a missing sign, not a defaced one — simply a smooth band of tilework where the name ought to have been, the cream-colored tiles unbroken, as if the place had been built deliberately to refuse identification." | | 1 | "The air changed the instant she crossed it — colder, but not the wet cold of underground London." | | 2 | "Her knees protested; she ignored them." | | 3 | "\"He's on his side.\" She didn't touch him — never touch, not before she'd looked twice — but she leaned close, studying the purplish bloom of settled blood." | | 4 | "Worn, yes, the soles thin — but the laces double-knotted, tight, the leather creased only at the ball of the foot." | | 5 | "\"There's one set of tracks in and out. Ours. No drag marks. No shuffle. So how did he get to the bottom of a forty-step stair without leaving a print, and why is the dust on his shoulders, here—\" she pointed, not touching, to the fine pale film across the dead man's coat, \"—when he's lying face-down to it?\"" | | 6 | "This was the part she trusted least to words and most to instinct — the thing that had made her a detective and not merely a careful person." | | 7 | "And there, at the edge of the platform where the rails should have run, no rails at all — just a black throat of tunnel and, set into the wall beside it, a wooden door." | | 8 | "As she neared the wood she felt the cold sharpen to a blade, and something in her chest tightened — not fear exactly, but recognition, the body's memory outrunning the mind's." | | 9 | "Its face was etched with markings she didn't recognize — angular, deliberate, the kind of symbols that wanted very badly to mean something." | | 10 | "Instead she straightened her cuffs, checked her watch out of pure habit, and committed every wrong detail to memory — the unwired bulb, the dustless shoes, the spinning needle, the door that breathed." | | 11 | "She bent, drew an evidence bag from her coat, and — gloved now, careful — lifted the small brass compass from the floor." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 564 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.024822695035460994 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0070921985815602835 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 100 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 100 | | mean | 13.25 | | std | 11.31 | | cv | 0.853 | | sampleLengths | | 0 | 33 | | 1 | 25 | | 2 | 24 | | 3 | 13 | | 4 | 17 | | 5 | 3 | | 6 | 14 | | 7 | 3 | | 8 | 6 | | 9 | 5 | | 10 | 37 | | 11 | 11 | | 12 | 7 | | 13 | 11 | | 14 | 53 | | 15 | 14 | | 16 | 5 | | 17 | 1 | | 18 | 5 | | 19 | 18 | | 20 | 16 | | 21 | 6 | | 22 | 3 | | 23 | 25 | | 24 | 13 | | 25 | 2 | | 26 | 20 | | 27 | 2 | | 28 | 6 | | 29 | 3 | | 30 | 3 | | 31 | 28 | | 32 | 16 | | 33 | 2 | | 34 | 32 | | 35 | 3 | | 36 | 15 | | 37 | 4 | | 38 | 3 | | 39 | 9 | | 40 | 5 | | 41 | 21 | | 42 | 7 | | 43 | 4 | | 44 | 18 | | 45 | 27 | | 46 | 59 | | 47 | 4 | | 48 | 2 | | 49 | 9 |
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| 60.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.43 | | totalSentences | 100 | | uniqueOpeners | 43 | |
| 45.05% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 74 | | matches | | 0 | "Instead she straightened her cuffs," |
| | ratio | 0.014 | |
| 84.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 74 | | matches | | 0 | "He was crouched beside a" | | 1 | "She was looking at the" | | 2 | "She filed that away and" | | 3 | "She ducked under the tape." | | 4 | "She kept walking." | | 5 | "Her knees protested; she ignored" | | 6 | "She didn't touch him —" | | 7 | "He had a good face" | | 8 | "It was the single most" | | 9 | "She moved down the body" | | 10 | "She gestured at the staircase" | | 11 | "she pointed, not touching, to" | | 12 | "She straightened and let her" | | 13 | "Her footsteps echoed strangely, returning" | | 14 | "She had spent three years" | | 15 | "She wasn't sure she could" | | 16 | "She crouched again and looked" | | 17 | "Its face was etched with" | | 18 | "She had made that mistake" | | 19 | "It never had." |
| | ratio | 0.338 | |
| 95.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 74 | | matches | | 0 | "The call had come in" | | 1 | "He was crouched beside a" | | 2 | "The tape sagged." | | 3 | "The turnstiles hadn't turned in" | | 4 | "Quinn didn't laugh." | | 5 | "She was looking at the" | | 6 | "The station had no name." | | 7 | "She filed that away and" | | 8 | "Reyes went on, rising and" | | 9 | "She ducked under the tape." | | 10 | "The air changed the instant" | | 11 | "A dry cold, like the" | | 12 | "The hair on her forearms" | | 13 | "She kept walking." | | 14 | "The platform opened up below" | | 15 | "A man, sixties perhaps, curled" | | 16 | "Reyes's interpretation hung in the" | | 17 | "Her knees protested; she ignored" | | 18 | "She didn't touch him —" | | 19 | "He had a good face" |
| | ratio | 0.73 | |
| 67.57% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 74 | | matches | | | ratio | 0.014 | |
| 14.65% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 7 | | matches | | 0 | "Not a missing sign, not a defaced one — simply a smooth band of tilework where the name ought to have been, the cream-colored tiles unbroken, as if the place ha…" | | 1 | "A dry cold, like the inside of a freezer, like something that had never known weather." | | 2 | "Her footsteps echoed strangely, returning to her a half-beat too late, as though the room were larger than it looked." | | 3 | "A warehouse in Deptford, a door that shouldn't have been there, and DS Morris stepping through it ahead of her with his torch raised, saying *clear* in his easy…" | | 4 | "Its face was etched with markings she didn't recognize — angular, deliberate, the kind of symbols that wanted very badly to mean something." | | 5 | "Slow, steady, ceaseless, pointing nowhere and then everywhere, as if magnetic north had simply ceased to exist." | | 6 | "Instead she straightened her cuffs, checked her watch out of pure habit, and committed every wrong detail to memory — the unwired bulb, the dustless shoes, the …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 26 | | tagDensity | 0.231 | | leniency | 0.462 | | rawRatio | 0 | | effectiveRatio | 0 | |