| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn said again [again]" |
| | dialogueSentences | 32 | | tagDensity | 0.531 | | leniency | 1 | | rawRatio | 0.059 | | effectiveRatio | 0.059 | |
| 90.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1030 | | totalAiIsmAdverbs | 2 | | found | | 0 | | adverb | "deliberately" | | count | 1 |
| | 1 | |
| | highlights | | 0 | "deliberately" | | 1 | "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) | |
| 56.31% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1030 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "blown wide" | | 1 | "fascinating" | | 2 | "etched" | | 3 | "silence" | | 4 | "measured" | | 5 | "fractured" | | 6 | "weight" | | 7 | "footsteps" |
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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 | 97 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 97 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 112 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1030 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 803 | | uniqueNames | 9 | | maxNameDensity | 1.25 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Transit | 2 | | Authority | 2 | | Fletcher | 4 | | London | 1 | | Underground | 1 | | Quinn | 10 | | Silence | 1 | | Kowalski | 1 | | Eva | 3 |
| | persons | | 0 | "Authority" | | 1 | "Fletcher" | | 2 | "Quinn" | | 3 | "Kowalski" | | 4 | "Eva" |
| | places | | | globalScore | 0.877 | | windowScore | 0.667 | |
| 55.66% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like the moment they decided to st" | | 1 | "looked like when they feared something ot" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.971 | | wordCount | 1030 | | matches | | 0 | "not in the cloudy way of an overdose, but sharp" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 112 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 20.2 | | std | 19.77 | | cv | 0.979 | | sampleLengths | | 0 | 6 | | 1 | 50 | | 2 | 38 | | 3 | 9 | | 4 | 17 | | 5 | 6 | | 6 | 23 | | 7 | 1 | | 8 | 64 | | 9 | 4 | | 10 | 7 | | 11 | 3 | | 12 | 21 | | 13 | 61 | | 14 | 30 | | 15 | 10 | | 16 | 66 | | 17 | 5 | | 18 | 1 | | 19 | 55 | | 20 | 15 | | 21 | 3 | | 22 | 1 | | 23 | 1 | | 24 | 7 | | 25 | 8 | | 26 | 62 | | 27 | 10 | | 28 | 33 | | 29 | 1 | | 30 | 26 | | 31 | 2 | | 32 | 40 | | 33 | 4 | | 34 | 19 | | 35 | 22 | | 36 | 17 | | 37 | 8 | | 38 | 7 | | 39 | 46 | | 40 | 23 | | 41 | 2 | | 42 | 20 | | 43 | 43 | | 44 | 4 | | 45 | 48 | | 46 | 9 | | 47 | 8 | | 48 | 3 | | 49 | 9 |
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| 98.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 97 | | matches | | 0 | "were folded" | | 1 | "been pulled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 135 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 112 | | ratio | 0 | | matches | (empty) | |
| 93.31% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 809 | | adjectiveStacks | 1 | | stackExamples | | 0 | "wide behind round glasses." |
| | adverbCount | 33 | | adverbRatio | 0.0407911001236094 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007416563658838072 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 112 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 112 | | mean | 9.2 | | std | 7.31 | | cv | 0.795 | | sampleLengths | | 0 | 6 | | 1 | 15 | | 2 | 22 | | 3 | 2 | | 4 | 5 | | 5 | 2 | | 6 | 4 | | 7 | 9 | | 8 | 19 | | 9 | 10 | | 10 | 3 | | 11 | 6 | | 12 | 6 | | 13 | 5 | | 14 | 6 | | 15 | 6 | | 16 | 13 | | 17 | 10 | | 18 | 1 | | 19 | 7 | | 20 | 7 | | 21 | 18 | | 22 | 5 | | 23 | 6 | | 24 | 21 | | 25 | 2 | | 26 | 2 | | 27 | 7 | | 28 | 3 | | 29 | 7 | | 30 | 5 | | 31 | 9 | | 32 | 6 | | 33 | 6 | | 34 | 9 | | 35 | 4 | | 36 | 11 | | 37 | 20 | | 38 | 5 | | 39 | 6 | | 40 | 13 | | 41 | 1 | | 42 | 10 | | 43 | 10 | | 44 | 14 | | 45 | 17 | | 46 | 9 | | 47 | 5 | | 48 | 21 | | 49 | 5 |
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| 87.80% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5535714285714286 | | totalSentences | 112 | | uniqueOpeners | 62 | |
| 45.05% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 74 | | matches | | 0 | "Deliberately, with the thumbs crossed." |
| | ratio | 0.014 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 74 | | matches | | 0 | "He'd been on the force" | | 1 | "She studied the man's hands" | | 2 | "They were folded across his" | | 3 | "She stood and moved along" | | 4 | "They were old London Underground" | | 5 | "She moved back to the" | | 6 | "His face was slack, but" | | 7 | "She'd seen enough of those." | | 8 | "She swept the torch along" | | 9 | "She pulled on a glove" | | 10 | "It spun once, twice, and" | | 11 | "She bagged it and kept" | | 12 | "She crouched again." | | 13 | "She heard it in the" | | 14 | "She rolled one of the" | | 15 | "She pointed the torch at" | | 16 | "he said, but his voice" | | 17 | "She raised one hand, palm" | | 18 | "Her hand lifted and tucked" | | 19 | "She'd also been doing this" |
| | ratio | 0.297 | |
| 95.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 74 | | matches | | 0 | "The body faced the wrong" | | 1 | "Quinn crouched beside it, her" | | 2 | "The Transit Authority hadn't run" | | 3 | "DS Fletcher said behind her" | | 4 | "He'd been on the force" | | 5 | "Quinn didn't answer." | | 6 | "She studied the man's hands" | | 7 | "They were folded across his" | | 8 | "Nobody arranged themselves like that" | | 9 | "Fletcher snapped his notebook shut" | | 10 | "She stood and moved along" | | 11 | "The torch beam swept the" | | 12 | "They were old London Underground" | | 13 | "A metre across, scrubbed clean." | | 14 | "Fletcher appeared at her shoulder" | | 15 | "Quinn touched the edge of" | | 16 | "The lines were smooth, finished." | | 17 | "She moved back to the" | | 18 | "Both shoes still on." | | 19 | "His face was slack, but" |
| | ratio | 0.73 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 74 | | matches | | 0 | "Whoever made these had done" | | 1 | "And, crucially, already inside a" |
| | ratio | 0.027 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 1 | | matches | | 0 | "A sound with weight and intention, slow and deliberate, footsteps on old wooden sleepers, coming from the part of the underground that, according to every Trans…" |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, but his voice had lost its certainty" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 1 | | fancyTags | | 0 | "Fletcher snapped (snap)" |
| | dialogueSentences | 32 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0.083 | | effectiveRatio | 0.063 | |