| 62.07% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "own torch pointed courteously [courteously]" | | 1 | "Pryce said slowly [slowly]" |
| | dialogueSentences | 29 | | tagDensity | 0.448 | | leniency | 0.897 | | rawRatio | 0.154 | | effectiveRatio | 0.138 | |
| 89.44% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1420 | | totalAiIsmAdverbs | 3 | | 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) | |
| 92.96% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1420 | | 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 | 81 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 81 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 95 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 3 | | totalWords | 1430 | | ratio | 0.002 | | matches | | 0 | "condensation, refrigeration unit" |
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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 | 24 | | wordCount | 1078 | | uniqueNames | 9 | | maxNameDensity | 0.83 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Ferdinand | 1 | | Street | 1 | | Harlow | 1 | | Quinn | 9 | | Owen | 1 | | Pryce | 8 | | September | 1 | | Peckham | 1 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Owen" | | 3 | "Pryce" | | 4 | "Morris" |
| | places | | 0 | "Ferdinand" | | 1 | "Street" | | 2 | "September" | | 3 | "Peckham" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.699 | | wordCount | 1430 | | matches | | 0 | "not colder, exactly, but older, the way air gets" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 33.26 | | std | 30.93 | | cv | 0.93 | | sampleLengths | | 0 | 20 | | 1 | 56 | | 2 | 53 | | 3 | 4 | | 4 | 67 | | 5 | 58 | | 6 | 65 | | 7 | 9 | | 8 | 81 | | 9 | 17 | | 10 | 138 | | 11 | 3 | | 12 | 39 | | 13 | 55 | | 14 | 1 | | 15 | 5 | | 16 | 10 | | 17 | 4 | | 18 | 22 | | 19 | 89 | | 20 | 47 | | 21 | 7 | | 22 | 46 | | 23 | 36 | | 24 | 23 | | 25 | 3 | | 26 | 27 | | 27 | 78 | | 28 | 30 | | 29 | 9 | | 30 | 66 | | 31 | 8 | | 32 | 3 | | 33 | 86 | | 34 | 4 | | 35 | 48 | | 36 | 12 | | 37 | 11 | | 38 | 6 | | 39 | 15 | | 40 | 6 | | 41 | 47 | | 42 | 16 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 81 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 160 | | matches | | 0 | "was waiting" | | 1 | "was doing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 1 | | flaggedSentences | 8 | | totalSentences | 96 | | ratio | 0.083 | | matches | | 0 | "At the bottom the air changed — not colder, exactly, but older, the way air gets when nothing has breathed it for eighty years." | | 1 | "And a staircase — a proper old spiral, iron, with a cage of rust around it — coming down out of the ceiling and ending eight feet above the floor, cut off where the surface works had removed everything above." | | 2 | "Her knees complained; forty-one was doing that now." | | 3 | "And around the body, in a rough circle three feet out from the head—" | | 4 | "Not spotless — old stains, a scuff at the elbow — but the nap of it lay flat and grey-free, and the soles of the dead man's shoes, tilted toward them, were dark and slick and clean as a wet road." | | 5 | "Not a shadow — a stain, an outline, sooty and precise, describing a doorway within the arch: two uprights, a lintel, a threshold, all of them charred into the brickwork as though a door had been there and had burned, and the brick behind had cooled around the memory of it." | | 6 | "Under the glass, the needle swung, hunted, hesitated—" | | 7 | "—and settled, hard, pointing at the burned outline on the bricked-up wall." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1081 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.01757631822386679 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004625346901017576 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 14.9 | | std | 15.25 | | cv | 1.024 | | sampleLengths | | 0 | 20 | | 1 | 19 | | 2 | 1 | | 3 | 24 | | 4 | 12 | | 5 | 38 | | 6 | 15 | | 7 | 4 | | 8 | 47 | | 9 | 20 | | 10 | 10 | | 11 | 23 | | 12 | 20 | | 13 | 5 | | 14 | 12 | | 15 | 6 | | 16 | 7 | | 17 | 40 | | 18 | 9 | | 19 | 18 | | 20 | 1 | | 21 | 4 | | 22 | 8 | | 23 | 14 | | 24 | 36 | | 25 | 17 | | 26 | 16 | | 27 | 95 | | 28 | 27 | | 29 | 3 | | 30 | 2 | | 31 | 8 | | 32 | 29 | | 33 | 1 | | 34 | 27 | | 35 | 8 | | 36 | 5 | | 37 | 14 | | 38 | 1 | | 39 | 5 | | 40 | 2 | | 41 | 8 | | 42 | 4 | | 43 | 6 | | 44 | 5 | | 45 | 11 | | 46 | 44 | | 47 | 45 | | 48 | 2 | | 49 | 4 |
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| 80.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5104166666666666 | | totalSentences | 96 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 68 | | matches | | 0 | "Her boots came down on" | | 1 | "He fell in beside her," | | 2 | "HE'S IN THE ARMY NOW." | | 3 | "He lay on his back" | | 4 | "He indicated a corner of" | | 5 | "Her knees complained; forty-one was" | | 6 | "She set her torch on" | | 7 | "She could read those tracks" | | 8 | "He looked for a long" | | 9 | "he said at last" | | 10 | "She lifted her torch, moved" | | 11 | "She stood, joints clicking, and" | | 12 | "Her stomach did something small" | | 13 | "She had written *condensation, refrigeration" | | 14 | "He fetched them." | | 15 | "She went back to the" | | 16 | "She drew it out into" | | 17 | "She palmed it into her" |
| | ratio | 0.265 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 68 | | matches | | 0 | "The hatch was in the" | | 1 | "Detective Harlow Quinn went down" | | 2 | "Her boots came down on" | | 3 | "DS Owen Pryce was waiting" | | 4 | "He fell in beside her," | | 5 | "Quinn said nothing and let" | | 6 | "The tunnel walls were tiled" | | 7 | "Every twenty feet a poster" | | 8 | "HE'S IN THE ARMY NOW." | | 9 | "The ticket hall opened out" | | 10 | "A wooden booth with the" | | 11 | "The body lay at the" | | 12 | "Pryce's crime scene officers had" | | 13 | "Fifties, maybe late forties." | | 14 | "He lay on his back" | | 15 | "The pool of blood under" | | 16 | "Pryce said, and Quinn heard" | | 17 | "He indicated a corner of" | | 18 | "Her knees complained; forty-one was" | | 19 | "She set her torch on" |
| | ratio | 0.691 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 68 | | matches | | 0 | "To his credit, he did" | | 1 | "—and settled, hard, pointing at" |
| | ratio | 0.029 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 2 | | matches | | 0 | "He lay on his back with his left arm folded under him and his right hand open, palm up, fingers curled loosely, as though he'd been holding something and had le…" | | 1 | "Not a shadow — a stain, an outline, sooty and precise, describing a doorway within the arch: two uprights, a lintel, a threshold, all of them charred into the b…" |
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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 | 8 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.276 | | leniency | 0.552 | | rawRatio | 0 | | effectiveRatio | 0 | |