| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "DC Pettigrew peeled away [away]" |
| | dialogueSentences | 39 | | tagDensity | 0.436 | | leniency | 0.872 | | rawRatio | 0.059 | | effectiveRatio | 0.051 | |
| 95.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1201 | | totalAiIsmAdverbs | 1 | | 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) | |
| 83.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1201 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "perfect" | | 1 | "weight" | | 2 | "etched" |
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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 | 0 | | narrationSentences | 73 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 73 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1215 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 86.63% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 789 | | uniqueNames | 10 | | maxNameDensity | 1.27 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 10 | | Road | 1 | | Met | 1 | | Pettigrew | 7 | | Male | 1 | | Morris | 1 | | Notes | 1 | | Camden | 2 | | One | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Met" | | 3 | "Pettigrew" | | 4 | "Morris" |
| | places | | | globalScore | 0.866 | | windowScore | 1 | |
| 51.96% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | glossingSentenceCount | 2 | | matches | | 0 | "as though reaching for the warped tiles of the old platform" | | 1 | "looked like dried insects, labelled in a" |
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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 | 1215 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 34.71 | | std | 24.4 | | cv | 0.703 | | sampleLengths | | 0 | 65 | | 1 | 40 | | 2 | 25 | | 3 | 38 | | 4 | 36 | | 5 | 10 | | 6 | 9 | | 7 | 78 | | 8 | 31 | | 9 | 10 | | 10 | 7 | | 11 | 72 | | 12 | 5 | | 13 | 65 | | 14 | 8 | | 15 | 16 | | 16 | 61 | | 17 | 51 | | 18 | 56 | | 19 | 23 | | 20 | 60 | | 21 | 4 | | 22 | 78 | | 23 | 9 | | 24 | 39 | | 25 | 67 | | 26 | 17 | | 27 | 35 | | 28 | 30 | | 29 | 32 | | 30 | 1 | | 31 | 23 | | 32 | 4 | | 33 | 76 | | 34 | 34 |
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| 90.84% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 73 | | matches | | 0 | "were packed" | | 1 | "been lifted" | | 2 | "been sold" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 135 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 95 | | ratio | 0.063 | | matches | | 0 | "Not the work of squatters — squatters didn't build counters from black lacquered wood or hang their wares on silver hooks." | | 1 | "The grime on the platform lay in one unbroken skin, disturbed only by the police cordon path, the anonymous caller's scuffed trainers by the stairwell, and a single set of prints belonging to the victim — arriving." | | 2 | "Near the dead man's outstretched right hand, something had burned a ring into the tile — a perfect circle, black-edged, no wider than a dinner plate." | | 3 | "The grey dust in its left pan formed a tiny heap, undisturbed — but the right pan held an indentation, a shallow bowl pressed into nothing, as though weight had sat there recently and been lifted away." | | 4 | "Twelve — the twelfth dark, shuttered, positioned exactly where the dead man had fallen." | | 5 | "She led him back to the first stall, to a dish of small brass objects — compasses, a dozen of them, faces etched with dense spiralling marks." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 788 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.025380710659898477 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006345177664974619 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 12.79 | | std | 9.77 | | cv | 0.764 | | sampleLengths | | 0 | 21 | | 1 | 25 | | 2 | 6 | | 3 | 9 | | 4 | 4 | | 5 | 14 | | 6 | 11 | | 7 | 15 | | 8 | 7 | | 9 | 10 | | 10 | 3 | | 11 | 2 | | 12 | 3 | | 13 | 23 | | 14 | 15 | | 15 | 13 | | 16 | 10 | | 17 | 13 | | 18 | 10 | | 19 | 3 | | 20 | 6 | | 21 | 15 | | 22 | 21 | | 23 | 10 | | 24 | 14 | | 25 | 6 | | 26 | 12 | | 27 | 7 | | 28 | 24 | | 29 | 5 | | 30 | 5 | | 31 | 2 | | 32 | 5 | | 33 | 33 | | 34 | 37 | | 35 | 2 | | 36 | 5 | | 37 | 11 | | 38 | 26 | | 39 | 9 | | 40 | 6 | | 41 | 9 | | 42 | 4 | | 43 | 8 | | 44 | 16 | | 45 | 7 | | 46 | 11 | | 47 | 37 | | 48 | 6 | | 49 | 16 |
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| 79.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.5263157894736842 | | totalSentences | 95 | | uniqueOpeners | 50 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 65 | | matches | | 0 | "Then she stopped, because the" | | 1 | "Then she photographed it, logged" |
| | ratio | 0.031 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 65 | | matches | | 0 | "He was young, eager, damp" | | 1 | "She crouched beside the body" | | 2 | "She didn't answer." | | 3 | "She was looking at the" | | 4 | "She'd assumed it was old" | | 5 | "It came off on her" | | 6 | "She held his gaze until" | | 7 | "She moved along the horseshoe," | | 8 | "She photographed it from three" | | 9 | "She almost walked past." | | 10 | "She'd seen a staged scene" | | 11 | "She'd never found a contractor's" | | 12 | "She stood, working it through" | | 13 | "She pointed with her pen" | | 14 | "She led him back to" | | 15 | "She lifted one with her" | | 16 | "It pointed, trembling, at the" | | 17 | "She looked at it for" | | 18 | "She clicked her torch on" |
| | ratio | 0.292 | |
| 83.08% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 65 | | matches | | 0 | "The body lay face-down between" | | 1 | "Detective Harlow Quinn ducked under" | | 2 | "Camden Road, sealed since the" | | 3 | "The Met's records called it" | | 4 | "The stalls said otherwise." | | 5 | "DC Pettigrew peeled away from" | | 6 | "He was young, eager, damp" | | 7 | "She crouched beside the body" | | 8 | "Pettigrew flipped a page" | | 9 | "Quinn lifted the dead man's" | | 10 | "The fingernails were packed with" | | 11 | "She didn't answer." | | 12 | "She was looking at the" | | 13 | "Quinn walked the arc slowly," | | 14 | "Jars of what looked like" | | 15 | "A scale of brass, impossibly" | | 16 | "Pettigrew said at her shoulder" | | 17 | "Quinn turned in place" | | 18 | "The grime on the platform" | | 19 | "Pettigrew's mouth opened, then shut." |
| | ratio | 0.754 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 2 | | matches | | 0 | "The body lay face-down between two stalls, arms flung wide as though reaching for the warped tiles of the old platform." | | 1 | "The grey dust in its left pan formed a tiny heap, undisturbed — but the right pan held an indentation, a shallow bowl pressed into nothing, as though weight had…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 39 | | tagDensity | 0.077 | | leniency | 0.154 | | rawRatio | 0.333 | | effectiveRatio | 0.051 | |