| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 34 | | tagDensity | 0.235 | | leniency | 0.471 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1934 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "slightly" | | 2 | "perfectly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 79.32% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1934 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "perfect" | | 1 | "shattered" | | 2 | "etched" | | 3 | "methodical" | | 4 | "aftermath" | | 5 | "scanning" | | 6 | "footsteps" | | 7 | "measured" |
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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 | 2 | | narrationSentences | 132 | | matches | | 0 | "n in wonder" | | 1 | "p in panic" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 132 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 158 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 31 | | totalWords | 1946 | | ratio | 0.016 | | matches | | 0 | "The alignment is accelerating. HM insists on attending the next opening despite the readings. I've told him the compass activity alone should be enough to postpone, but he won't hear it." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 98.32% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1548 | | uniqueNames | 15 | | maxNameDensity | 1.03 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 16 | | Camden | 4 | | Osei | 6 | | Mayfair | 1 | | High | 1 | | Street | 1 | | Hale | 4 | | Belgravia | 1 | | Marcus | 3 | | Lock | 1 | | English | 2 | | Morris | 3 | | Deptford | 1 | | One | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Osei" | | 3 | "Hale" | | 4 | "Marcus" | | 5 | "Morris" | | 6 | "One" |
| | places | | 0 | "Camden" | | 1 | "Mayfair" | | 2 | "High" | | 3 | "Street" | | 4 | "Deptford" |
| | globalScore | 0.983 | | windowScore | 1 | |
| 72.68% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 97 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like mercury, but it moved against" | | 1 | "looked like the aftermath of a shockwave" | | 2 | "felt like it was generating its own gra" |
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| 45.84% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 1.542 | | wordCount | 1946 | | matches | | 0 | "not pain, not fear, but something Quinn had seen only once before" | | 1 | "not fear, but something Quinn had seen only once before" | | 2 | "not north but toward the tunnel mouth behind her" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 158 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 36.72 | | std | 34.27 | | cv | 0.933 | | sampleLengths | | 0 | 80 | | 1 | 25 | | 2 | 46 | | 3 | 95 | | 4 | 41 | | 5 | 54 | | 6 | 23 | | 7 | 3 | | 8 | 70 | | 9 | 7 | | 10 | 21 | | 11 | 86 | | 12 | 15 | | 13 | 1 | | 14 | 14 | | 15 | 12 | | 16 | 6 | | 17 | 52 | | 18 | 134 | | 19 | 4 | | 20 | 111 | | 21 | 30 | | 22 | 24 | | 23 | 20 | | 24 | 26 | | 25 | 6 | | 26 | 7 | | 27 | 54 | | 28 | 67 | | 29 | 5 | | 30 | 15 | | 31 | 2 | | 32 | 16 | | 33 | 93 | | 34 | 76 | | 35 | 6 | | 36 | 10 | | 37 | 111 | | 38 | 19 | | 39 | 53 | | 40 | 3 | | 41 | 77 | | 42 | 47 | | 43 | 11 | | 44 | 27 | | 45 | 8 | | 46 | 81 | | 47 | 5 | | 48 | 37 | | 49 | 19 |
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| 81.34% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 9 | | totalSentences | 132 | | matches | | 0 | "been disturbed" | | 1 | "been frozen" | | 2 | "was gone " | | 3 | "been gone" | | 4 | "were scabbed" | | 5 | "been converted" | | 6 | "been torn" | | 7 | "was etched" | | 8 | "was gone" | | 9 | "been dropped" | | 10 | "were covered" | | 11 | "been open" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 262 | | matches | | 0 | "were hiding" | | 1 | "was admitting" | | 2 | "was generating" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 20 | | semicolonCount | 0 | | flaggedSentences | 14 | | totalSentences | 158 | | ratio | 0.089 | | matches | | 0 | "The abandoned station beneath Camden smelled of standing water and something else — copper, maybe, or burnt sugar." | | 1 | "His expression was the problem — not pain, not fear, but something Quinn had seen only once before." | | 2 | "The platform had collected decades of dust and debris — broken tiles, pigeon feathers, the dessicated husk of a rat — but in the immediate vicinity of the corpse, the dust had been disturbed in a pattern." | | 3 | "The door was gone — had been gone for years by the look of the hinges, which were scabbed with rust — and the room beyond had been converted into something that made Quinn stop at the threshold." | | 4 | "Fabric canopies in deep jewel tones — amethyst, sapphire, a red so dark it was nearly black — hung from hooks driven into the ceiling." | | 5 | "The face was etched with symbols she didn't recognize — not any alphabet she'd encountered in eighteen years of forgery cases, smuggling rings, or organized crime." | | 6 | "She pulled out her phone and photographed the room in methodical sections — walls, floor, ceiling, each table, each jar." | | 7 | "Bone — off-white, smooth, slightly warm to the touch." | | 8 | "Something happens — something that freezes a look of awe on his face and stops his heart." | | 9 | "Something had radiated outward from Marcus Hale — or inward toward him." | | 10 | "Near the entrance — a steel door that opened onto a narrow staircase leading up to the Camden Lock basement — she found a book." | | 11 | "Not identical — Morris's eyes had been open, and they'd carried something closer to terror than wonder — but the same fundamental quality." | | 12 | "Quinn had accepted it at the time because accepting it was easier than the alternative, which was admitting that the marks on the floor of that warehouse in Deptford — concentric, radiating, perfectly symmetrical — had no rational explanation." | | 13 | "But Quinn had noticed something the lights couldn't reveal — the shadow under the nearest trestle table fell in the wrong direction." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1534 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 42 | | adverbRatio | 0.027379400260756193 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0045632333767926985 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 158 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 158 | | mean | 12.32 | | std | 9.27 | | cv | 0.753 | | sampleLengths | | 0 | 26 | | 1 | 32 | | 2 | 18 | | 3 | 4 | | 4 | 13 | | 5 | 12 | | 6 | 19 | | 7 | 12 | | 8 | 6 | | 9 | 9 | | 10 | 19 | | 11 | 24 | | 12 | 21 | | 13 | 3 | | 14 | 2 | | 15 | 18 | | 16 | 1 | | 17 | 7 | | 18 | 11 | | 19 | 20 | | 20 | 3 | | 21 | 7 | | 22 | 16 | | 23 | 13 | | 24 | 25 | | 25 | 23 | | 26 | 3 | | 27 | 3 | | 28 | 5 | | 29 | 11 | | 30 | 30 | | 31 | 8 | | 32 | 13 | | 33 | 7 | | 34 | 3 | | 35 | 18 | | 36 | 15 | | 37 | 37 | | 38 | 2 | | 39 | 20 | | 40 | 12 | | 41 | 15 | | 42 | 1 | | 43 | 2 | | 44 | 12 | | 45 | 7 | | 46 | 5 | | 47 | 6 | | 48 | 14 | | 49 | 38 |
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| 66.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4177215189873418 | | totalSentences | 158 | | uniqueOpeners | 66 | |
| 55.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 121 | | matches | | 0 | "Away from the light source," | | 1 | "Then she kept walking." |
| | ratio | 0.017 | |
| 94.38% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 121 | | matches | | 0 | "She couldn't place it." | | 1 | "Her worn leather watch caught" | | 2 | "She'd been asleep forty minutes" | | 3 | "He was on his back" | | 4 | "His expression was the problem" | | 5 | "She crouched beside the body" | | 6 | "She preferred shadow." | | 7 | "He was young, thorough, and" | | 8 | "She lifted Hale's left hand." | | 9 | "She raised the hand closer" | | 10 | "She stood and backed up" | | 11 | "She left him to arrange" | | 12 | "She didn't touch it." | | 13 | "She knelt and unwrapped one." | | 14 | "She held it flat in" | | 15 | "She rotated ninety degrees." | | 16 | "She pulled out her phone" | | 17 | "His face had changed." | | 18 | "She stepped past him and" | | 19 | "She walked back to the" |
| | ratio | 0.314 | |
| 50.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 99 | | totalSentences | 121 | | matches | | 0 | "The platform tiles still bore" | | 1 | "Detective Harlow Quinn ducked under" | | 2 | "The abandoned station beneath Camden" | | 3 | "She couldn't place it." | | 4 | "Sergeant Osei called from further" | | 5 | "Quinn stepped over a bundle" | | 6 | "Her worn leather watch caught" | | 7 | "Quarter past two in the" | | 8 | "She'd been asleep forty minutes" | | 9 | "The body lay at the" | | 10 | "A man, mid-fifties, dressed in" | | 11 | "He was on his back" | | 12 | "His expression was the problem" | | 13 | "A dead man's face frozen" | | 14 | "She crouched beside the body" | | 15 | "The overhead fluorescents her team" | | 16 | "She preferred shadow." | | 17 | "Shadow told you where things" | | 18 | "Osei said, appearing at her" | | 19 | "He was young, thorough, and" |
| | ratio | 0.818 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 121 | | matches | (empty) | | ratio | 0 | |
| 89.55% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 67 | | technicalSentenceCount | 5 | | matches | | 0 | "A man, mid-fifties, dressed in a tweed coat that looked expensive enough to belong in Mayfair rather than twenty meters beneath Camden High Street." | | 1 | "The disturbance radiated outward from the body in concentric rings, like ripples in a pond that had been frozen mid-expansion." | | 2 | "The door was gone — had been gone for years by the look of the hinges, which were scabbed with rust — and the room beyond had been converted into something that…" | | 3 | "Something happens — something that freezes a look of awe on his face and stops his heart." | | 4 | "Quinn had accepted it at the time because accepting it was easier than the alternative, which was admitting that the marks on the floor of that warehouse in Dep…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "the doorway tablet pressed (press)" | | 1 | "The English notes (note)" |
| | dialogueSentences | 34 | | tagDensity | 0.147 | | leniency | 0.294 | | rawRatio | 0.4 | | effectiveRatio | 0.118 | |