| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 955 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | | 2 | | adverb | "deliberately" | | count | 1 |
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| | highlights | | 0 | "slightly" | | 1 | "carefully" | | 2 | "deliberately" |
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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) | |
| 73.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 955 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "etched" | | 1 | "standard" | | 2 | "silence" | | 3 | "trembled" |
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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 | 74 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 74 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 948 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.47% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 638 | | uniqueNames | 9 | | maxNameDensity | 1.41 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Quinn | 1 | | Ffrench | 7 | | Tube | 1 | | Morris | 1 | | Victorian | 1 | | Scratch | 1 | | Dark | 1 | | Ashworth | 2 | | Harlow | 9 |
| | persons | | 0 | "Quinn" | | 1 | "Ffrench" | | 2 | "Morris" | | 3 | "Scratch" | | 4 | "Ashworth" | | 5 | "Harlow" |
| | places | (empty) | | globalScore | 0.795 | | windowScore | 0.833 | |
| 47.96% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 2 | | matches | | 0 | "as if grasping at something invisible" | | 1 | "looked like Ffrench's size tens" |
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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 | 948 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 101 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 23.12 | | std | 20.52 | | cv | 0.887 | | sampleLengths | | 0 | 54 | | 1 | 9 | | 2 | 39 | | 3 | 16 | | 4 | 24 | | 5 | 5 | | 6 | 2 | | 7 | 43 | | 8 | 15 | | 9 | 57 | | 10 | 3 | | 11 | 19 | | 12 | 29 | | 13 | 34 | | 14 | 4 | | 15 | 7 | | 16 | 50 | | 17 | 21 | | 18 | 7 | | 19 | 20 | | 20 | 52 | | 21 | 3 | | 22 | 7 | | 23 | 25 | | 24 | 21 | | 25 | 9 | | 26 | 1 | | 27 | 58 | | 28 | 11 | | 29 | 5 | | 30 | 71 | | 31 | 3 | | 32 | 62 | | 33 | 2 | | 34 | 62 | | 35 | 9 | | 36 | 2 | | 37 | 14 | | 38 | 19 | | 39 | 41 | | 40 | 13 |
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| 91.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 74 | | matches | | 0 | "been worn" | | 1 | "were pushed" | | 2 | "been removed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 109 | | matches | (empty) | |
| 1.41% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 101 | | ratio | 0.05 | | matches | | 0 | "The man's clothes were expensive—tailored wool coat, leather shoes that had barely been worn." | | 1 | "Etched into the face were symbols she didn't recognise—nested circles broken by angular lines, nothing like standard cartographic markings." | | 2 | "The tiles here were different from the rest—newer, if you could call 1920s tile newer." | | 3 | "Not a tattoo—too fresh, the skin still raised and angry." | | 4 | "Not random—the same symbol, repeated, carved into the ceramic with something sharp." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 648 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.030864197530864196 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.009259259259259259 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 9.39 | | std | 6.86 | | cv | 0.731 | | sampleLengths | | 0 | 9 | | 1 | 26 | | 2 | 19 | | 3 | 2 | | 4 | 7 | | 5 | 11 | | 6 | 11 | | 7 | 17 | | 8 | 16 | | 9 | 13 | | 10 | 1 | | 11 | 3 | | 12 | 7 | | 13 | 5 | | 14 | 2 | | 15 | 15 | | 16 | 15 | | 17 | 13 | | 18 | 5 | | 19 | 10 | | 20 | 5 | | 21 | 14 | | 22 | 13 | | 23 | 14 | | 24 | 3 | | 25 | 2 | | 26 | 3 | | 27 | 2 | | 28 | 1 | | 29 | 3 | | 30 | 19 | | 31 | 9 | | 32 | 11 | | 33 | 9 | | 34 | 3 | | 35 | 1 | | 36 | 11 | | 37 | 19 | | 38 | 4 | | 39 | 7 | | 40 | 5 | | 41 | 5 | | 42 | 8 | | 43 | 8 | | 44 | 1 | | 45 | 1 | | 46 | 22 | | 47 | 21 | | 48 | 6 | | 49 | 1 |
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| 90.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5544554455445545 | | totalSentences | 101 | | uniqueOpeners | 56 | |
| 53.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 62 | | matches | | 0 | "Still believed the job was" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 62 | | matches | | 0 | "Her leather watch caught on" | | 1 | "She'd counted them on the" | | 2 | "His arms were spread at" | | 3 | "She knelt beside the body." | | 4 | "His face held an expression" | | 5 | "She pulled on nitrile gloves" | | 6 | "She turned the compass over." | | 7 | "It stopped pointing north and" | | 8 | "She stood and walked toward" | | 9 | "She stopped at the platform" | | 10 | "She watched it for a" | | 11 | "She crossed back to the" | | 12 | "He'd seen something behind that" |
| | ratio | 0.21 | |
| 80.97% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 62 | | matches | | 0 | "The stairs down smelled of" | | 1 | "Harlow Quinn clicked her torch" | | 2 | "Her leather watch caught on" | | 3 | "She'd counted them on the" | | 4 | "The body lay near the" | | 5 | "A man, mid-fifties, grey hair" | | 6 | "His arms were spread at" | | 7 | "DC Ffrench crouched three metres" | | 8 | "Harlow moved closer, her torch" | | 9 | "Ffrench stood, his knees cracking." | | 10 | "She knelt beside the body." | | 11 | "The man's clothes were expensive—tailored" | | 12 | "His face held an expression" | | 13 | "Harlow tilted her head, studying" | | 14 | "She pulled on nitrile gloves" | | 15 | "A brass compass." | | 16 | "The casing had that green-blue" | | 17 | "She turned the compass over." | | 18 | "The back was smooth, unmarked." | | 19 | "It stopped pointing north and" |
| | ratio | 0.758 | |
| 80.65% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 62 | | matches | | 0 | "Either way, it had stopped" |
| | ratio | 0.016 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "His arms were spread at odd angles, palms up, fingers curled as if grasping at something invisible." | | 1 | "The casing had that green-blue verdigris that took decades to form." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 2 | | matches | | 0 | "Harlow moved, her torch beam tracking the ground around the body" | | 1 | "Harlow walked, her torch picking out details Ffrench had missed" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |