| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1017 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 95.08% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1017 | | totalAiIsms | 1 | | found | | | highlights | | |
| 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 | 78 | | matches | | 0 | "was proud" | | 1 | "was afraid" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 78 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1027 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 966 | | uniqueNames | 16 | | maxNameDensity | 0.62 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Herrera" | | discoveredNames | | Camden | 2 | | Tomás | 1 | | Herrera | 4 | | Morris | 3 | | Uber | 1 | | Tube | 1 | | Royal | 1 | | Command | 1 | | Performance | 1 | | Hackney | 1 | | Peckham | 1 | | Quinn | 6 | | Saint | 1 | | Christopher | 1 | | Whitechapel | 1 | | Protocol | 3 |
| | persons | | 0 | "Tomás" | | 1 | "Herrera" | | 2 | "Morris" | | 3 | "Quinn" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Protocol" |
| | places | | 0 | "Hackney" | | 1 | "Peckham" | | 2 | "Whitechapel" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1027 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 35.41 | | std | 29.22 | | cv | 0.825 | | sampleLengths | | 0 | 26 | | 1 | 56 | | 2 | 98 | | 3 | 36 | | 4 | 10 | | 5 | 7 | | 6 | 63 | | 7 | 10 | | 8 | 72 | | 9 | 2 | | 10 | 71 | | 11 | 4 | | 12 | 66 | | 13 | 1 | | 14 | 35 | | 15 | 8 | | 16 | 11 | | 17 | 66 | | 18 | 11 | | 19 | 17 | | 20 | 73 | | 21 | 44 | | 22 | 8 | | 23 | 35 | | 24 | 100 | | 25 | 32 | | 26 | 33 | | 27 | 27 | | 28 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 78 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 151 | | matches | | 0 | "was running" | | 1 | "was slowing" | | 2 | "was going" | | 3 | "wasn't breaking" | | 4 | "was still running " | | 5 | "was going" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 1 | | flaggedSentences | 7 | | totalSentences | 82 | | ratio | 0.085 | | matches | | 0 | "The coat was slowing her — sodden at the hem, heavy as chainmail across the shoulders — but she wasn't about to shed it." | | 1 | "\"Quinn to dispatch.\" Her voice came out level; she was proud of that." | | 2 | "Three years on the job and she could tell the difference between bad signal and something else — something that crowded the frequencies when she got near certain people, certain places, the way a storm pressed down on the ears before it broke." | | 3 | "Quinn saw the flash of something at his throat — a medal on a chain, silver in the wet light — and then he was gone into the dark mouth of a side road she didn't know the name of." | | 4 | "Somewhere ahead he was still running — she could hear his soles slap — and then, abruptly, she couldn't." | | 5 | "And beyond the doorway, a set of stairs going down, slick with rain that had followed them in, and on the first step — unmistakable — a dark spatter the size of a ten-pence piece." | | 6 | "Herrera's name, third from the top, because he was the softest — ex-paramedic, nothing to lose left to lose, the kind of man who would talk if you found the right pressure." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 958 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.025052192066805846 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0020876826722338203 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 12.52 | | std | 10.61 | | cv | 0.847 | | sampleLengths | | 0 | 23 | | 1 | 3 | | 2 | 20 | | 3 | 24 | | 4 | 7 | | 5 | 5 | | 6 | 26 | | 7 | 11 | | 8 | 7 | | 9 | 22 | | 10 | 32 | | 11 | 13 | | 12 | 23 | | 13 | 4 | | 14 | 6 | | 15 | 4 | | 16 | 3 | | 17 | 43 | | 18 | 20 | | 19 | 4 | | 20 | 4 | | 21 | 2 | | 22 | 32 | | 23 | 40 | | 24 | 2 | | 25 | 5 | | 26 | 7 | | 27 | 14 | | 28 | 26 | | 29 | 19 | | 30 | 3 | | 31 | 1 | | 32 | 7 | | 33 | 4 | | 34 | 20 | | 35 | 35 | | 36 | 1 | | 37 | 4 | | 38 | 13 | | 39 | 3 | | 40 | 15 | | 41 | 8 | | 42 | 11 | | 43 | 9 | | 44 | 13 | | 45 | 16 | | 46 | 28 | | 47 | 5 | | 48 | 6 | | 49 | 17 |
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| 71.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.5 | | totalSentences | 82 | | uniqueOpeners | 41 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 70 | | matches | | 0 | "Somewhere ahead he was still" | | 1 | "Somewhere in it, a bell" | | 2 | "Then she reached down, picked" |
| | ratio | 0.043 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 70 | | matches | | 0 | "She had her radio in" | | 1 | "He ran like a man" | | 2 | "Her voice came out level;" | | 3 | "She wasn't breaking up." | | 4 | "She swallowed the thought." | | 5 | "She could smell hot oil" | | 6 | "Her boots hit the slick" | | 7 | "She keyed the radio." | | 8 | "She looked up for a" | | 9 | "She clipped the radio to" | | 10 | "She had been afraid in" | | 11 | "It had not been there" | | 12 | "She did not pick it" | | 13 | "She thought about the notebook" | | 14 | "She thought about the scar" | | 15 | "She thought about Morris." | | 16 | "She looked at it for" |
| | ratio | 0.243 | |
| 95.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 51 | | totalSentences | 70 | | matches | | 0 | "Rain came down in sheets," | | 1 | "Quinn was running." | | 2 | "She had her radio in" | | 3 | "The coat was slowing her" | | 4 | "The coat had the notebook" | | 5 | "The notebook had the names." | | 6 | "He ran like a man" | | 7 | "That was the part that" | | 8 | "Herrera was cutting left where" | | 9 | "Her voice came out level;" | | 10 | "The radio coughed static." | | 11 | "She wasn't breaking up." | | 12 | "The radio was." | | 13 | "The same static she'd heard" | | 14 | "She swallowed the thought." | | 15 | "Herrera cut across the street," | | 16 | "Quinn saw the flash of" | | 17 | "Brick walls narrowed around her." | | 18 | "The rain sounded different here," | | 19 | "She could smell hot oil" |
| | ratio | 0.729 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 70 | | matches | | 0 | "To the left, bins." | | 1 | "To the right, a recessed" |
| | ratio | 0.029 | |
| 31.25% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 5 | | matches | | 0 | "Rain came down in sheets, turning the Camden pavement into a black mirror that swallowed the streetlamps and spit them back up sideways." | | 1 | "Three years on the job and she could tell the difference between bad signal and something else — something that crowded the frequencies when she got near certai…" | | 2 | "And beyond the doorway, a set of stairs going down, slick with rain that had followed them in, and on the first step — unmistakable — a dark spatter the size of…" | | 3 | "Posters peeling in strips, advertising cigarettes that weren't sold anymore, a Royal Command Performance from 1952." | | 4 | "Herrera's name, third from the top, because he was the softest — ex-paramedic, nothing to lose left to lose, the kind of man who would talk if you found the rig…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |