| 46.15% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 1 | | adverbTags | | 0 | "his voice bounced strangely [strangely]" |
| | dialogueSentences | 13 | | tagDensity | 0.231 | | leniency | 0.462 | | rawRatio | 0.333 | | effectiveRatio | 0.154 | |
| 84.13% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 945 | | totalAiIsmAdverbs | 3 | | 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) | |
| 73.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 945 | | totalAiIsms | 5 | | found | | 0 | | | 1 | | | 2 | | | 3 | | word | "the last thing" | | count | 1 |
| | 4 | |
| | highlights | | 0 | "glint" | | 1 | "footsteps" | | 2 | "echoed" | | 3 | "the last thing" | | 4 | "flickered" |
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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 | 53 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 53 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 63 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 939 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 96.81% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 846 | | uniqueNames | 10 | | maxNameDensity | 1.06 | | worstName | "Herrera" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Herrera" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 2 | | Herrera | 9 | | God-knew-what | 1 | | Quinn | 9 | | Underground | 1 | | London | 1 | | Tube | 1 | | Morris | 3 |
| | persons | | 0 | "Nest" | | 1 | "Herrera" | | 2 | "Quinn" | | 3 | "Tube" | | 4 | "Morris" |
| | places | | | globalScore | 0.968 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like nothing" | | 1 | "something like ozone before a storm" | | 2 | "quite triumph" |
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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 | 939 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 63 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 31.3 | | std | 27.36 | | cv | 0.874 | | sampleLengths | | 0 | 51 | | 1 | 40 | | 2 | 7 | | 3 | 98 | | 4 | 41 | | 5 | 6 | | 6 | 16 | | 7 | 49 | | 8 | 74 | | 9 | 11 | | 10 | 43 | | 11 | 3 | | 12 | 21 | | 13 | 79 | | 14 | 31 | | 15 | 25 | | 16 | 91 | | 17 | 4 | | 18 | 35 | | 19 | 6 | | 20 | 13 | | 21 | 6 | | 22 | 32 | | 23 | 56 | | 24 | 10 | | 25 | 4 | | 26 | 6 | | 27 | 60 | | 28 | 10 | | 29 | 11 |
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| 92.02% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 53 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 147 | | matches | | 0 | "was chasing" | | 1 | "was lying" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 63 | | ratio | 0.063 | | matches | | 0 | "Her radio crackled at her hip—dispatch asking for her location—but she didn't answer." | | 1 | "\"Detective, I really wouldn't—\" his voice bounced strangely off the tiles, \"—I really wouldn't finish that sentence if I were you.\"" | | 2 | "The smell hit her first—copper and incense and something like ozone before a storm." | | 3 | "Something flickered across his face—recognition, maybe pity—gone before she could read it properly." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 481 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.029106029106029108 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.006237006237006237 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 63 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 63 | | mean | 14.9 | | std | 9.07 | | cv | 0.608 | | sampleLengths | | 0 | 18 | | 1 | 33 | | 2 | 13 | | 3 | 21 | | 4 | 6 | | 5 | 7 | | 6 | 3 | | 7 | 24 | | 8 | 13 | | 9 | 23 | | 10 | 13 | | 11 | 6 | | 12 | 16 | | 13 | 22 | | 14 | 19 | | 15 | 6 | | 16 | 16 | | 17 | 30 | | 18 | 19 | | 19 | 17 | | 20 | 5 | | 21 | 10 | | 22 | 4 | | 23 | 21 | | 24 | 17 | | 25 | 11 | | 26 | 19 | | 27 | 16 | | 28 | 8 | | 29 | 3 | | 30 | 21 | | 31 | 12 | | 32 | 32 | | 33 | 14 | | 34 | 21 | | 35 | 31 | | 36 | 19 | | 37 | 6 | | 38 | 16 | | 39 | 26 | | 40 | 7 | | 41 | 2 | | 42 | 40 | | 43 | 4 | | 44 | 13 | | 45 | 22 | | 46 | 6 | | 47 | 13 | | 48 | 6 | | 49 | 3 |
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| 78.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5079365079365079 | | totalSentences | 63 | | uniqueOpeners | 32 | |
| 64.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 52 | | matches | | 0 | "Then the sound, low murmuring" |
| | ratio | 0.019 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 52 | | matches | | 0 | "He moved fast for a" | | 1 | "He didn't stop." | | 2 | "He cut left down an" | | 3 | "Her radio crackled at her" | | 4 | "He disappeared down a stairwell" | | 5 | "She'd read the reports." | | 6 | "She drew her torch instead" | | 7 | "his voice bounced strangely off" | | 8 | "He was lying." | | 9 | "She'd built a career on" | | 10 | "She thought of Morris." | | 11 | "She thumbed off the torch" |
| | ratio | 0.231 | |
| 65.77% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 52 | | matches | | 0 | "Quinn kept thirty feet between" | | 1 | "He moved fast for a" | | 2 | "Herrera ran like the second" | | 3 | "He didn't stop." | | 4 | "He cut left down an" | | 5 | "Her radio crackled at her" | | 6 | "Backup meant paperwork, meant explaining" | | 7 | "Morris used to tell her" | | 8 | "Herrera vaulted a low fence," | | 9 | "Quinn followed, palms scraping brick," | | 10 | "Herrera called back, not even" | | 11 | "He disappeared down a stairwell" | | 12 | "The chain lay in the" | | 13 | "Quinn stood at the top" | | 14 | "She'd read the reports." | | 15 | "Officers who'd gone into old" | | 16 | "Stations that weren't on any" | | 17 | "She drew her torch instead" | | 18 | "The stairwell dumped her into" | | 19 | "Herrera's footsteps echoed ahead, unhurried" |
| | ratio | 0.788 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 27.03% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 6 | | matches | | 0 | "Quinn followed, palms scraping brick, and landed in a service yard that smelled of bins and old fryer oil." | | 1 | "He disappeared down a stairwell she hadn't noticed, one of those ignored entrances to the old Underground network, chained shut with a padlock that should have …" | | 2 | "Then the sound, low murmuring in a dozen languages, the clink of coin that didn't look like any coin she recognised." | | 3 | "Every instinct that had kept her alive eighteen years told her to radio it in, call for backup, treat this like any other unlicensed market raid." | | 4 | "Morris's face surfaced in her mind, the last thing she remembered clearly before the blank three hours that ended with him gone and her standing alone in a tunn…" | | 5 | "A bell somewhere in the market rang, three notes, and the murmur of the crowd shifted, wary, stalls beginning to shutter with a speed that felt rehearsed." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "Herrera called back, not even turning," |
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| 73.08% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "Herrera called back (call back)" |
| | dialogueSentences | 13 | | tagDensity | 0.077 | | leniency | 0.154 | | rawRatio | 1 | | effectiveRatio | 0.154 | |