| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn replied exasperatingly [exasperatingly]" |
| | dialogueSentences | 14 | | tagDensity | 0.786 | | leniency | 1 | | rawRatio | 0.091 | | effectiveRatio | 0.091 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 781 | | 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) | |
| 48.78% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 781 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "chill" | | 1 | "facade" | | 2 | "standard" | | 3 | "porcelain" | | 4 | "footsteps" | | 5 | "potential" | | 6 | "crystal" | | 7 | "mosaic" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 63 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 63 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 66 | | 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 | 784 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 1.41% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 673 | | uniqueNames | 18 | | maxNameDensity | 2.97 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 20 | | Underground | 1 | | London | 1 | | Detective | 5 | | Jasper | 5 | | Camden | 1 | | Johnstone | 4 | | MacDouble | 2 | | Eva | 2 | | Fame | 1 | | Fortune | 1 | | Eidechsa | 1 | | Elice | 1 | | Mosaic | 1 | | Cassata | 1 | | Nicaraguan | 1 | | Mattle | 1 | | Harlow | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Detective" | | 2 | "Jasper" | | 3 | "Johnstone" | | 4 | "MacDouble" | | 5 | "Eva" | | 6 | "Nicaraguan" | | 7 | "Mattle" | | 8 | "Harlow" |
| | places | | 0 | "London" | | 1 | "Fame" | | 2 | "Mosaic" |
| | globalScore | 0.014 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | 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 | 784 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 66 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 27.03 | | std | 20.41 | | cv | 0.755 | | sampleLengths | | 0 | 56 | | 1 | 73 | | 2 | 35 | | 3 | 39 | | 4 | 30 | | 5 | 27 | | 6 | 32 | | 7 | 53 | | 8 | 36 | | 9 | 30 | | 10 | 16 | | 11 | 6 | | 12 | 8 | | 13 | 40 | | 14 | 7 | | 15 | 18 | | 16 | 3 | | 17 | 21 | | 18 | 5 | | 19 | 32 | | 20 | 4 | | 21 | 38 | | 22 | 21 | | 23 | 7 | | 24 | 14 | | 25 | 8 | | 26 | 85 | | 27 | 33 | | 28 | 7 |
| |
| 94.12% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 63 | | matches | | 0 | "been called" | | 1 | "was required" |
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| 83.04% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 114 | | matches | | 0 | "was wanting" | | 1 | "was scowling" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 5 | | flaggedSentences | 5 | | totalSentences | 66 | | ratio | 0.076 | | matches | | 0 | "Award violations to;" | | 1 | "- Fame - Fortune - Eidechsa In conclusion; spectrum shifts." | | 2 | "A cloaked portrait idea; the nunette, Elice in black." | | 3 | "They were unable to parse the clue further than this, however; Jasper belched and letting forth forth a Nicaraguan upwards fart." | | 4 | "They bid temporary goodnight; and Johnstone and Mattle hastily departed." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 671 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.014903129657228018 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.007451564828614009 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 66 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 66 | | mean | 11.88 | | std | 7.64 | | cv | 0.644 | | sampleLengths | | 0 | 25 | | 1 | 17 | | 2 | 14 | | 3 | 21 | | 4 | 10 | | 5 | 42 | | 6 | 12 | | 7 | 10 | | 8 | 13 | | 9 | 27 | | 10 | 12 | | 11 | 18 | | 12 | 12 | | 13 | 27 | | 14 | 10 | | 15 | 12 | | 16 | 10 | | 17 | 12 | | 18 | 20 | | 19 | 18 | | 20 | 3 | | 21 | 36 | | 22 | 10 | | 23 | 16 | | 24 | 4 | | 25 | 16 | | 26 | 6 | | 27 | 8 | | 28 | 12 | | 29 | 11 | | 30 | 12 | | 31 | 5 | | 32 | 7 | | 33 | 18 | | 34 | 3 | | 35 | 6 | | 36 | 15 | | 37 | 5 | | 38 | 13 | | 39 | 3 | | 40 | 7 | | 41 | 3 | | 42 | 10 | | 43 | 8 | | 44 | 8 | | 45 | 9 | | 46 | 9 | | 47 | 4 | | 48 | 21 | | 49 | 7 |
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| 96.97% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.7121212121212122 | | totalSentences | 66 | | uniqueOpeners | 47 | |
| 57.47% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 58 | | matches | | 0 | "Perhaps outside analysis was required" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 58 | | matches | | 0 | "His mirth fell flat as" | | 1 | "They had been called to" | | 2 | "They entered the dilapidated station" | | 3 | "he indicated an exploded set" | | 4 | "She reeked at a deep" | | 5 | "They were unable to parse" | | 6 | "They bid temporary goodnight; and" | | 7 | "She toed off her tearing" | | 8 | "She'd pondered on this a" | | 9 | "She mulled on the optimum" | | 10 | "Her choice came to Eva," |
| | ratio | 0.19 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 38 | | totalSentences | 58 | | matches | | 0 | "Detective Quinn stepped out of" | | 1 | "The dead of night hung" | | 2 | "His mirth fell flat as" | | 3 | "They had been called to" | | 4 | "They entered the dilapidated station" | | 5 | "SOCO had already been and" | | 6 | "The wandering officers, Johnstone and" | | 7 | "Johnstone pointed with his pencil" | | 8 | "he indicated an exploded set" | | 9 | "MacDouble added, as Quinn regarded" | | 10 | "Quinn explained, decentering the young" | | 11 | "The extremely disused tunnel yawned" | | 12 | "Quinn extracted her torch and" | | 13 | "An onerous aroma hung in" | | 14 | "She reeked at a deep" | | 15 | "Curiosity driving her, Quinn marched" | | 16 | "Foot rattling, the choreographed stress" | | 17 | "Quinn shook her head." | | 18 | "Quinn uttered in a low" | | 19 | "Quinn replied exasperatingly" |
| | ratio | 0.655 | |
| 86.21% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 58 | | matches | | | ratio | 0.017 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 1 | | matches | | 0 | "Detective Quinn stepped out of the unmarked police car, her worn leather shoes crunching on the gravel path that led to the abandoned Underground station." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 4 | | fancyTags | | 0 | "They had (have)" | | 1 | "MacDouble added (add)" | | 2 | "Quinn explained (explain)" | | 3 | "Eva muttered (mutter)" |
| | dialogueSentences | 14 | | tagDensity | 0.357 | | leniency | 0.714 | | rawRatio | 0.8 | | effectiveRatio | 0.571 | |