| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.02% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1671 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "sharply" | | 1 | "softly" | | 2 | "slightly" |
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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) | |
| 46.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1671 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "echoes" | | 1 | "flickered" | | 2 | "glint" | | 3 | "etched" | | 4 | "weight" | | 5 | "standard" | | 6 | "scanned" | | 7 | "pulsed" | | 8 | "processed" | | 9 | "shattered" | | 10 | "pulse" | | 11 | "traced" | | 12 | "warmth" | | 13 | "shimmered" |
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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 | 111 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 111 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | 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 | 1667 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 87.38% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 1517 | | uniqueNames | 7 | | maxNameDensity | 1.25 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 19 | | Tube | 1 | | Camden | 1 | | Kowalski | 1 | | London | 1 | | Eva | 12 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" |
| | places | | | globalScore | 0.874 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 101 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared clustered beneath a single point, and the repositioned stalls formed a closed geometric shape" |
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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 | 1667 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 118 | | matches | (empty) | |
| 75.70% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 57.48 | | std | 23.85 | | cv | 0.415 | | sampleLengths | | 0 | 130 | | 1 | 44 | | 2 | 68 | | 3 | 25 | | 4 | 80 | | 5 | 73 | | 6 | 43 | | 7 | 52 | | 8 | 54 | | 9 | 57 | | 10 | 31 | | 11 | 103 | | 12 | 58 | | 13 | 29 | | 14 | 75 | | 15 | 73 | | 16 | 26 | | 17 | 64 | | 18 | 46 | | 19 | 29 | | 20 | 55 | | 21 | 47 | | 22 | 57 | | 23 | 15 | | 24 | 78 | | 25 | 58 | | 26 | 57 | | 27 | 78 | | 28 | 62 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 111 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 239 | | matches | (empty) | |
| 70.22% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 118 | | ratio | 0.025 | | matches | | 0 | "The cloth carried the same sigil pattern etched on the compass face—protective wards against something she had never catalogued in eighteen years on the force." | | 1 | "Quinn scanned the platform once more and spotted a discarded cord caught on a stall leg three meters away—its knot pattern matched the snapped ends." | | 2 | "A second set of footprints climbed the steps—smaller tread, deeper heel strike—while every official diagram showed the suspect descending only." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1524 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 44 | | adverbRatio | 0.028871391076115485 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.006561679790026247 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 14.13 | | std | 6.66 | | cv | 0.471 | | sampleLengths | | 0 | 20 | | 1 | 12 | | 2 | 6 | | 3 | 12 | | 4 | 8 | | 5 | 18 | | 6 | 17 | | 7 | 9 | | 8 | 17 | | 9 | 11 | | 10 | 19 | | 11 | 10 | | 12 | 15 | | 13 | 8 | | 14 | 25 | | 15 | 14 | | 16 | 21 | | 17 | 10 | | 18 | 15 | | 19 | 18 | | 20 | 6 | | 21 | 14 | | 22 | 22 | | 23 | 20 | | 24 | 24 | | 25 | 12 | | 26 | 12 | | 27 | 25 | | 28 | 14 | | 29 | 29 | | 30 | 23 | | 31 | 14 | | 32 | 7 | | 33 | 8 | | 34 | 7 | | 35 | 13 | | 36 | 21 | | 37 | 13 | | 38 | 9 | | 39 | 20 | | 40 | 11 | | 41 | 12 | | 42 | 5 | | 43 | 9 | | 44 | 22 | | 45 | 8 | | 46 | 16 | | 47 | 30 | | 48 | 15 | | 49 | 22 |
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| 49.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.2542372881355932 | | totalSentences | 118 | | uniqueOpeners | 30 | |
| 30.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 108 | | matches | | 0 | "Then the pulse resumed, and" |
| | ratio | 0.009 | |
| 90.37% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 108 | | matches | | 0 | "Her leather watch shifted against" | | 1 | "She descended the metal steps," | | 2 | "She adjusted the strap with" | | 3 | "She pulled a pair of" | | 4 | "She crossed to the third" | | 5 | "She brushed dust from a" | | 6 | "She bent and lifted it" | | 7 | "She stood again and scanned" | | 8 | "She pressed two fingers against" | | 9 | "She checked the wristwatch on" | | 10 | "Her own watch showed 2:43." | | 11 | "She noted three sets of" | | 12 | "She followed the wall with" | | 13 | "She closed the compartment and" | | 14 | "She ran a fingertip along" | | 15 | "She straightened and stepped over" | | 16 | "She turned back to the" | | 17 | "She walked to that exact" | | 18 | "She removed the bone token" | | 19 | "She repeated the test with" |
| | ratio | 0.324 | |
| 20.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 95 | | totalSentences | 108 | | matches | | 0 | "Detective Harlow Quinn stood at" | | 1 | "Her leather watch shifted against" | | 2 | "She descended the metal steps," | | 3 | "The air thickened with damp" | | 4 | "Quinn moved closer and crouched" | | 5 | "Eva Kowalski waited on the" | | 6 | "The satchel strap dug into" | | 7 | "She adjusted the strap with" | | 8 | "Quinn straightened and stepped around" | | 9 | "A faint smear of green" | | 10 | "The needle inside that compass" | | 11 | "She pulled a pair of" | | 12 | "Quinn turned the bone token" | | 13 | "She crossed to the third" | | 14 | "Blood pooled beneath the shoulders" | | 15 | "The station floor around the" | | 16 | "Those stalls now leaned against" | | 17 | "She brushed dust from a" | | 18 | "The film did not match" | | 19 | "Quinn lifted a charred scrap" |
| | ratio | 0.88 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 108 | | matches | (empty) | | ratio | 0 | |
| 66.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 75 | | technicalSentenceCount | 8 | | matches | | 0 | "Detective Harlow Quinn stood at the top of the rusting escalator that plunged into the abandoned Tube station beneath Camden." | | 1 | "She brushed dust from a metal rail beside the tracks and found the same verdigris film on her finger that marked the compass casing." | | 2 | "The newest set matched her own tread but two older trails veered sharply toward a maintenance alcove and ended in abrupt smudges, as though feet had been lifted…" | | 3 | "This time she noticed the shimmer bent the blood pools inward, as if drawn toward a single unseen point directly above the center body." | | 4 | "She noted the middle set showed no displacement of earlier dust layers, as if the owner had arrived through an aperture that left no tracks until the final mete…" | | 5 | "A short passage led to a second platform edge that overlooked the main tracks from twenty meters higher." | | 6 | "Her gloved fingers met a cool, taut surface that gave slightly, then released a puff of air carrying the same metallic scent." | | 7 | "The wind from the street above met her at the top landing, carrying city noise that drowned the faint pulse of the emergency lights below." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0 | | effectiveRatio | 0 | |