| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 15 | | tagDensity | 0.467 | | leniency | 0.933 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.32% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1713 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "carefully" |
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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) | |
| 94.16% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1713 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 103 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 103 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "happens to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 111 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 27 | | totalWords | 1728 | | ratio | 0.016 | | matches | | 0 | "moves every full moon, abandoned stations, bone token to get in, don't ask me twice, Detective, I like my bones where they are." | | 1 | "Follow. Go back." | | 2 | "unexplained" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1533 | | uniqueNames | 17 | | maxNameDensity | 0.65 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Euston | 1 | | Road | 1 | | Quinn | 10 | | London | 2 | | Morris | 3 | | Bermondsey | 1 | | Victorian | 1 | | Northern | 1 | | Tube | 1 | | Underground | 1 | | Veil | 1 | | Market | 1 | | Detective | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 2 | | Herrera | 2 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Tomás" | | 5 | "Herrera" |
| | places | | 0 | "Euston" | | 1 | "Road" | | 2 | "London" | | 3 | "Bermondsey" | | 4 | "Tube" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 84.26% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.157 | | wordCount | 1728 | | matches | | 0 | "not hostile, not yet, but with the practised approach of a doorkeeper" | | 1 | "not yet, but with the practised approach of a doorkeeper" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 111 | | matches | | 0 | "understood that she" | | 1 | "saw that its" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 41.14 | | std | 29.26 | | cv | 0.711 | | sampleLengths | | 0 | 18 | | 1 | 95 | | 2 | 21 | | 3 | 38 | | 4 | 44 | | 5 | 38 | | 6 | 62 | | 7 | 4 | | 8 | 50 | | 9 | 9 | | 10 | 93 | | 11 | 74 | | 12 | 6 | | 13 | 58 | | 14 | 78 | | 15 | 25 | | 16 | 93 | | 17 | 66 | | 18 | 95 | | 19 | 11 | | 20 | 53 | | 21 | 3 | | 22 | 73 | | 23 | 59 | | 24 | 26 | | 25 | 91 | | 26 | 23 | | 27 | 29 | | 28 | 7 | | 29 | 60 | | 30 | 2 | | 31 | 61 | | 32 | 37 | | 33 | 9 | | 34 | 15 | | 35 | 6 | | 36 | 65 | | 37 | 12 | | 38 | 42 | | 39 | 42 | | 40 | 23 | | 41 | 12 |
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| 91.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 103 | | matches | | 0 | "was layered" | | 1 | "been buried" | | 2 | "been accustomed" | | 3 | "been closed" |
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| 64.50% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 246 | | matches | | 0 | "were presenting" | | 1 | "was making" | | 2 | "was looking" | | 3 | "was not running" | | 4 | "was vanishing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 1 | | flaggedSentences | 10 | | totalSentences | 111 | | ratio | 0.09 | | matches | | 0 | "Quinn caught a flash of face — unnervingly smooth, the features arranged with the same slightly-wrong symmetry as a shop mannequin — and then he was off again, moving faster than the movement of his legs seemed to warrant." | | 1 | "The pavement simply opened beneath him — a maintenance grille, a broken railing, a flight of concrete steps descending into the dark — and he went down it like water down a drain." | | 2 | "Somewhere down there, a long way down, something was making a sound like a market — voices, a murmur of barter and haggling, the clink of glass, a woman laughing." | | 3 | "She had been alone the whole chase — no backup, no response on the radio, no uniforms closing in from the flanks." | | 4 | "She had never found bravery to be a useful concept in the moment; it was a word other people used afterwards to dress up a decision you'd made because there was nothing else to do." | | 5 | "Municipal, originally — a service access to the old Northern line tunnels." | | 6 | "Trestle tables and handcarts and stalls built out of old Underground signage lined both sides of the platform, and the place was full — crammed, humming, close with bodies and breath and smoke that curled in colours she had no name for." | | 7 | "People — the word did a lot of work here — moved between the stalls." | | 8 | "Every instinct she had — and they were good instincts, they had kept her alive through eighteen years of doors that needed kicking — was now telling her two opposite things at once." | | 9 | "A man detached himself from a stall selling things in stoppered bottles and moved to intercept her — not hostile, not yet, but with the practised approach of a doorkeeper." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1526 | | adjectiveStacks | 1 | | stackExamples | | 0 | "single worst procedural decision" |
| | adverbCount | 51 | | adverbRatio | 0.033420707732634336 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.009174311926605505 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 111 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 111 | | mean | 15.57 | | std | 12.69 | | cv | 0.815 | | sampleLengths | | 0 | 16 | | 1 | 2 | | 2 | 32 | | 3 | 27 | | 4 | 3 | | 5 | 33 | | 6 | 7 | | 7 | 14 | | 8 | 7 | | 9 | 4 | | 10 | 27 | | 11 | 5 | | 12 | 39 | | 13 | 4 | | 14 | 27 | | 15 | 7 | | 16 | 25 | | 17 | 2 | | 18 | 20 | | 19 | 8 | | 20 | 7 | | 21 | 4 | | 22 | 7 | | 23 | 10 | | 24 | 33 | | 25 | 9 | | 26 | 8 | | 27 | 19 | | 28 | 25 | | 29 | 11 | | 30 | 30 | | 31 | 6 | | 32 | 6 | | 33 | 3 | | 34 | 22 | | 35 | 37 | | 36 | 6 | | 37 | 4 | | 38 | 35 | | 39 | 14 | | 40 | 5 | | 41 | 22 | | 42 | 12 | | 43 | 7 | | 44 | 6 | | 45 | 31 | | 46 | 2 | | 47 | 23 | | 48 | 23 | | 49 | 22 |
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| 78.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.5045045045045045 | | totalSentences | 111 | | uniqueOpeners | 56 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 94 | | matches | | 0 | "Of course it did." | | 1 | "Somewhere down there, a long" | | 2 | "Then, twenty yards ahead, she" | | 3 | "Then she stopped." | | 4 | "Then, slowly, he reached into" |
| | ratio | 0.053 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 94 | | matches | | 0 | "Her lungs burned." | | 1 | "She keyed her radio as" | | 2 | "It had been doing that" | | 3 | "She thought of Morris." | | 4 | "She thought of him three" | | 5 | "She put more speed into" | | 6 | "Her worn leather watch, the" | | 7 | "She was alone." | | 8 | "She had been alone the" | | 9 | "She took the first step" | | 10 | "She had never found bravery" | | 11 | "She counted them, because counting" | | 12 | "She was looking at it" | | 13 | "He was not running any" | | 14 | "He had led her here." | | 15 | "She stopped walking." | | 16 | "She thought: if I walk" | | 17 | "I have tonight." | | 18 | "I have this one shot" | | 19 | "She thought: if I go" |
| | ratio | 0.266 | |
| 77.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 94 | | matches | | 0 | "Rain came sideways off the" | | 1 | "The suspect was forty yards" | | 2 | "Quinn hit the horn line" | | 3 | "Her lungs burned." | | 4 | "She keyed her radio as" | | 5 | "The radio coughed static and" | | 6 | "It had been doing that" | | 7 | "Quinn caught a flash of" | | 8 | "She thought of Morris." | | 9 | "She thought of him three" | | 10 | "She put more speed into" | | 11 | "The suspect turned left, off" | | 12 | "Her worn leather watch, the" | | 13 | "The streetlights here buzzed a" | | 14 | "Water ran in the gutters" | | 15 | "Halfway down, he dropped." | | 16 | "That was the only word" | | 17 | "The pavement simply opened beneath" | | 18 | "Quinn reached the top of" | | 19 | "This air smelled of damp" |
| | ratio | 0.766 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 94 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 10 | | matches | | 0 | "The suspect was forty yards ahead, a pale streak in a dark coat, cutting across the traffic with the loose, boneless gait of someone who had never once worried …" | | 1 | "It had been doing that all week, as though the airwaves in this part of London had developed a texture, something thick and uncooperative that swallowed signal." | | 2 | "She thought of him three years ago in a stairwell in Bermondsey, alone, with something that had left marks the pathologist had refused to put in writing." | | 3 | "Whatever was down those stairs was down there by itself, with her, and going into it would be the single worst procedural decision of a career that had so far p…" | | 4 | "The steps were concrete, industrial, slick with a runoff that didn't taste of rain when a drop of it hit her lip." | | 5 | "A man with a crow on his shoulder looked up at her and looked away again with the specific incuriosity of a crowd that had already decided she wasn't interestin…" | | 6 | "Go back.* The market noise filled the space between them: the clink of coins that rang wrong, the haggle, the woman's laugh again, closer now, and beneath it al…" | | 7 | "He was young, mid-twenties, olive-skinned, short dark curls plastered to his forehead with damp, and he held himself like someone who had once been accustomed t…" | | 8 | "Behind him the crowd churned and the suspect's dark coat was vanishing into the far end of the platform, toward a tiled corridor that led deeper into the tunnel…" | | 9 | "Rainwater dripped from her coat onto the old tiled floor of a station that had been closed since before she was born, and somewhere in the crowd a thing laughed…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 15 | | tagDensity | 0.467 | | leniency | 0.933 | | rawRatio | 0 | | effectiveRatio | 0 | |