| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "Herrera said quietly [quietly]" |
| | dialogueSentences | 22 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.125 | | effectiveRatio | 0.091 | |
| 94.15% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1709 | | 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) | |
| 82.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1709 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "streaming" | | 1 | "weight" | | 2 | "whisper" | | 3 | "could feel" | | 4 | "warmth" | | 5 | "pulse" |
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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 | 0 | | narrationSentences | 107 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 107 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 121 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1723 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1436 | | uniqueNames | 14 | | maxNameDensity | 0.77 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | High | 1 | | Street | 1 | | Harlow | 1 | | Quinn | 11 | | Peckham | 1 | | Morris | 6 | | Victorian | 1 | | London | 1 | | Bermondsey | 3 | | Tube | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Herrera" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Victorian" | | 4 | "London" | | 5 | "Bermondsey" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 1 | | matches | | 0 | "smelled like a medieval apothecary had exp" |
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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 | 1723 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 121 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 39.16 | | std | 34.88 | | cv | 0.891 | | sampleLengths | | 0 | 77 | | 1 | 39 | | 2 | 10 | | 3 | 6 | | 4 | 106 | | 5 | 67 | | 6 | 4 | | 7 | 3 | | 8 | 32 | | 9 | 70 | | 10 | 16 | | 11 | 104 | | 12 | 2 | | 13 | 47 | | 14 | 93 | | 15 | 11 | | 16 | 84 | | 17 | 92 | | 18 | 73 | | 19 | 11 | | 20 | 94 | | 21 | 17 | | 22 | 12 | | 23 | 9 | | 24 | 10 | | 25 | 76 | | 26 | 4 | | 27 | 13 | | 28 | 31 | | 29 | 76 | | 30 | 84 | | 31 | 6 | | 32 | 11 | | 33 | 14 | | 34 | 71 | | 35 | 46 | | 36 | 7 | | 37 | 46 | | 38 | 45 | | 39 | 5 | | 40 | 1 | | 41 | 3 | | 42 | 88 | | 43 | 7 |
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| 82.31% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 107 | | matches | | 0 | "been kicked" | | 1 | "being caught " | | 2 | "was gone" | | 3 | "been transformed" | | 4 | "was abandoned" | | 5 | "been polished" | | 6 | "been found" | | 7 | "been disciplined" |
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| 13.95% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 215 | | matches | | 0 | "was going" | | 1 | "was selling" | | 2 | "was counting" | | 3 | "was leaving" | | 4 | "was heading" | | 5 | "was watching" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 121 | | ratio | 0.058 | | matches | | 0 | "She saw it in his shoulders — a hitch, a shift of weight — and she smelled blood, copper-dark and wrong beneath the wet stone smell." | | 1 | "She caught a glimpse of a face — young, thin, terrified in a way that had nothing to do with being caught — and then he dropped." | | 2 | "Everything else — the older engine, the one that had driven her through twenty years of the worst nights London had to offer, the engine that had kept running after Morris went into a warehouse in Bermondsey and did not come out — said go." | | 3 | "Tiled walls in bottle green and cream, curved soot-streaked vaulting, the old roundel still visible under layers of grime — but the platform had been transformed." | | 4 | "A chalked board advertised BANNED TINCTURES — WHISPER OIL — SECOND SIGHT, HALF MOON ONLY." | | 5 | "He was heading for the tunnel — for the northbound line, or what had been the northbound line before it was abandoned and bricked and forgotten by everyone except the people down here." | | 6 | "The faces slid past — the wrong eyes, the wrong teeth, the wrong number of everything — and the lanterns swung and the drum kept time and the tunnel mouth grew larger." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1429 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.02589223233030091 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.007697690692792162 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 121 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 121 | | mean | 14.24 | | std | 12.02 | | cv | 0.844 | | sampleLengths | | 0 | 20 | | 1 | 18 | | 2 | 39 | | 3 | 7 | | 4 | 32 | | 5 | 10 | | 6 | 6 | | 7 | 15 | | 8 | 19 | | 9 | 6 | | 10 | 27 | | 11 | 3 | | 12 | 36 | | 13 | 20 | | 14 | 3 | | 15 | 26 | | 16 | 18 | | 17 | 3 | | 18 | 1 | | 19 | 3 | | 20 | 5 | | 21 | 27 | | 22 | 2 | | 23 | 1 | | 24 | 29 | | 25 | 8 | | 26 | 11 | | 27 | 19 | | 28 | 6 | | 29 | 10 | | 30 | 9 | | 31 | 7 | | 32 | 35 | | 33 | 8 | | 34 | 45 | | 35 | 2 | | 36 | 11 | | 37 | 21 | | 38 | 15 | | 39 | 5 | | 40 | 4 | | 41 | 26 | | 42 | 9 | | 43 | 9 | | 44 | 40 | | 45 | 6 | | 46 | 5 | | 47 | 13 | | 48 | 19 | | 49 | 15 |
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| 63.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.4297520661157025 | | totalSentences | 121 | | uniqueOpeners | 52 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 94 | | matches | | 0 | "Then he smiled, ruefully." | | 1 | "Somewhere behind her, a stallholder" | | 2 | "Somewhere inside her shirt, next" |
| | ratio | 0.032 | |
| 75.32% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 94 | | matches | | 0 | "She keyed her radio as" | | 1 | "She tore free and kept" | | 2 | "Her left knee, the one" | | 3 | "She ignored it." | | 4 | "She saw it in his" | | 5 | "He pressed a hand to" | | 6 | "He was hurt." | | 7 | "He looked back at her." | | 8 | "She caught a glimpse of" | | 9 | "She had no backup within" | | 10 | "She had a suspect who" | | 11 | "It was a Tube station." | | 12 | "Her hand went to her" | | 13 | "She did not draw it." | | 14 | "It had been in the" | | 15 | "She had read the word" | | 16 | "Her suspect was thirty yards" | | 17 | "He had his hand clamped" | | 18 | "He was heading for the" | | 19 | "She saw them clearly now" |
| | ratio | 0.362 | |
| 61.06% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 94 | | matches | | 0 | "Rain came down in sheets," | | 1 | "Detective Harlow Quinn ran, coat" | | 2 | "She keyed her radio as" | | 3 | "Static, then a voice drowned" | | 4 | "The suspect vaulted a low" | | 5 | "Quinn hurdled it after him," | | 6 | "She tore free and kept" | | 7 | "Her left knee, the one" | | 8 | "She ignored it." | | 9 | "The side street was narrow," | | 10 | "The suspect slowed." | | 11 | "She saw it in his" | | 12 | "He pressed a hand to" | | 13 | "He was hurt." | | 14 | "He looked back at her." | | 15 | "She caught a glimpse of" | | 16 | "Quinn skidded to the edge" | | 17 | "The smell that rose was" | | 18 | "Music came up the stairwell" | | 19 | "A low drum, a fiddle," |
| | ratio | 0.798 | |
| 53.19% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 94 | | matches | | | ratio | 0.011 | |
| 26.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 8 | | matches | | 0 | "Fifty yards ahead, the suspect cut between a shuttered kebab shop and a rack of dripping umbrellas, moving with the loose, unhurried economy of a man who knew e…" | | 1 | "She had a suspect who had bled on a wall and fled into a hole in the ground beneath Camden, into a place that smelled like a medieval apothecary had exploded in…" | | 2 | "Everything else — the older engine, the one that had driven her through twenty years of the worst nights London had to offer, the engine that had kept running a…" | | 3 | "The amber light came from torches in iron brackets, real flame, guttering in a draft that smelled of the deep earth." | | 4 | "She saw them clearly now and wished she hadn't: a woman whose eyes were solid black from lid to lid, a child with a fox's ears, a tall figure in a long coat tha…" | | 5 | "Around his neck, on a length of worn cord, hung a silver medallion that had been polished by years of thumbs: Saint Christopher, the patron of travellers." | | 6 | "Morris, who had gone into a room in Bermondsey and had been found three days later in a place he could not physically have reached, with a bone token in his poc…" | | 7 | "Somewhere inside her shirt, next to the warm disc of bone and the folded photograph of a dead man, her warrant card felt very small and very thin, a laminated s…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0 | | effectiveRatio | 0 | |