| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 2 | | adverbTags | | 0 | "She looked around [around]" | | 1 | "She turned back [back]" |
| | dialogueSentences | 57 | | tagDensity | 0.158 | | leniency | 0.316 | | rawRatio | 0.222 | | effectiveRatio | 0.07 | |
| 96.65% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1494 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 60.00% | 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) | |
| 63.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1494 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "gloom" | | 3 | "pulse" | | 4 | "echoed" | | 5 | "footsteps" | | 6 | "tracing" | | 7 | "etched" | | 8 | "calculated" |
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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 | 1 | | narrationSentences | 61 | | matches | | |
| 96.02% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 61 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1478 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 688 | | uniqueNames | 9 | | maxNameDensity | 2.18 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 15 | | Marcus | 1 | | Webb | 12 | | Cross | 2 | | Metropolitan | 1 | | Police | 1 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Marcus" | | 3 | "Webb" | | 4 | "Cross" | | 5 | "Police" | | 6 | "Morris" |
| | places | | | globalScore | 0.41 | | windowScore | 0.167 | |
| 41.30% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 2 | | matches | | 0 | "seemed reluctant to commit to" | | 1 | "as if expecting something to descend from the darkness" |
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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 | 1478 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 109 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 25.05 | | std | 19.85 | | cv | 0.792 | | sampleLengths | | 0 | 62 | | 1 | 9 | | 2 | 38 | | 3 | 2 | | 4 | 14 | | 5 | 59 | | 6 | 62 | | 7 | 4 | | 8 | 50 | | 9 | 3 | | 10 | 48 | | 11 | 40 | | 12 | 5 | | 13 | 16 | | 14 | 45 | | 15 | 13 | | 16 | 54 | | 17 | 29 | | 18 | 23 | | 19 | 7 | | 20 | 13 | | 21 | 56 | | 22 | 4 | | 23 | 2 | | 24 | 16 | | 25 | 12 | | 26 | 40 | | 27 | 9 | | 28 | 51 | | 29 | 47 | | 30 | 1 | | 31 | 52 | | 32 | 18 | | 33 | 34 | | 34 | 29 | | 35 | 3 | | 36 | 2 | | 37 | 45 | | 38 | 8 | | 39 | 39 | | 40 | 5 | | 41 | 55 | | 42 | 10 | | 43 | 37 | | 44 | 36 | | 45 | 5 | | 46 | 17 | | 47 | 1 | | 48 | 5 | | 49 | 51 |
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| 93.76% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 61 | | matches | | 0 | "were folded" | | 1 | "been sealed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 117 | | matches | (empty) | |
| 64.22% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 109 | | ratio | 0.028 | | matches | | 0 | "The abandoned Tube station smelt of wet concrete and something else—something copper-sweet that Harlow Quinn had learned to associate with the worst kind of discovery." | | 1 | "She retrieved a pen from her jacket and used it to lift the fabric, revealing an impression pressed into the skin—a circular shape with what appeared to be symbols around its edge." | | 2 | "The copper-sweet smell was stronger here, mingling with something else—something that made the fine hairs on her arms stand at attention." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 696 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.028735632183908046 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.010057471264367816 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 13.56 | | std | 10.41 | | cv | 0.767 | | sampleLengths | | 0 | 25 | | 1 | 18 | | 2 | 19 | | 3 | 9 | | 4 | 3 | | 5 | 20 | | 6 | 15 | | 7 | 2 | | 8 | 11 | | 9 | 3 | | 10 | 20 | | 11 | 21 | | 12 | 7 | | 13 | 11 | | 14 | 10 | | 15 | 18 | | 16 | 3 | | 17 | 16 | | 18 | 15 | | 19 | 4 | | 20 | 12 | | 21 | 38 | | 22 | 3 | | 23 | 19 | | 24 | 29 | | 25 | 11 | | 26 | 25 | | 27 | 4 | | 28 | 5 | | 29 | 16 | | 30 | 10 | | 31 | 12 | | 32 | 3 | | 33 | 20 | | 34 | 13 | | 35 | 7 | | 36 | 47 | | 37 | 3 | | 38 | 6 | | 39 | 11 | | 40 | 9 | | 41 | 23 | | 42 | 7 | | 43 | 2 | | 44 | 11 | | 45 | 16 | | 46 | 8 | | 47 | 32 | | 48 | 4 | | 49 | 2 |
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| 89.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5412844036697247 | | totalSentences | 109 | | uniqueOpeners | 59 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 58 | | matches | | 0 | "She ducked beneath the yellow" | | 1 | "He held a torch at" | | 2 | "His hands were folded across" | | 3 | "His expression held confusion." | | 4 | "She moved around the body," | | 5 | "She had seen that file" | | 6 | "She retrieved a pen from" | | 7 | "She pointed with the pen." | | 8 | "His breath caught." | | 9 | "She looked around the platform," | | 10 | "She turned back to face" | | 11 | "She pulled a pair of" | | 12 | "She stood and stripped off" | | 13 | "She paused at the threshold" |
| | ratio | 0.241 | |
| 46.21% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 48 | | totalSentences | 58 | | matches | | 0 | "The abandoned Tube station smelt" | | 1 | "She ducked beneath the yellow" | | 2 | "The timepiece left a brief" | | 3 | "DC Marcus Webb." | | 4 | "He held a torch at" | | 5 | "Webb's mouth worked around words" | | 6 | "The platform stretched before them," | | 7 | "Water dripped somewhere in the" | | 8 | "Quinn counted her footsteps out" | | 9 | "The body lay between the" | | 10 | "His hands were folded across" | | 11 | "Webb consulted his notebook, the" | | 12 | "Webb lowered his voice, though" | | 13 | "Quinn crouched beside the body," | | 14 | "Sebastian Cross had died with" | | 15 | "His expression held confusion." | | 16 | "She moved around the body," | | 17 | "The concrete between the tracks" | | 18 | "The question made Webb shift" | | 19 | "Quinn's jaw tightened." |
| | ratio | 0.828 | |
| 86.21% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 58 | | matches | | 0 | "Either Cross had walked to" |
| | ratio | 0.017 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 6 | | matches | | 0 | "Water dripped somewhere in the darkness beyond the torchlight, a metronomic pulse that had probably echoed through these tunnels for decades." | | 1 | "Male, mid-thirties by the look of him, dressed in a suit that cost more than Quinn's monthly salary." | | 2 | "No blood pooling beneath him, despite that copper-sweet smell that had greeted her at the entrance." | | 3 | "Sebastian Cross had died with his eyes open, staring at the curved ceiling of the tunnel as if expecting something to descend from the darkness." | | 4 | "A file that contained photographs of DS Morris's body, discovered in circumstances that had never been adequately explained." | | 5 | "The copper-sweet smell was stronger here, mingling with something else—something that made the fine hairs on her arms stand at attention." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 3 | | matches | | 0 | "Quinn straightened, her mind already working through possibilities" | | 1 | "She looked around, her gaze sweeping across the cracked tiles and discarded debris" | | 2 | "Quinn walked, her sharp eyes cataloguing details" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |