| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 8 | | tagDensity | 0.625 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1086 | | totalAiIsmAdverbs | 2 | | 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) | |
| 72.38% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1086 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "shattered" | | 1 | "stomach" | | 2 | "footsteps" | | 3 | "velvet" | | 4 | "familiar" | | 5 | "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 | 1 | | narrationSentences | 49 | | matches | | |
| 55.39% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 49 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 53 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 56 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 1094 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 1056 | | uniqueNames | 13 | | maxNameDensity | 0.76 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | Quinn | 8 | | Raven | 1 | | Nest | 2 | | Bayham | 1 | | Street | 1 | | Morris | 2 | | Town | 1 | | God | 1 | | Veil | 1 | | Market | 1 | | Detective | 1 | | Harlow | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Morris" | | 3 | "Harlow" |
| | places | | 0 | "Camden" | | 1 | "Bayham" | | 2 | "Street" | | 3 | "Town" |
| | globalScore | 1 | | windowScore | 1 | |
| 28.05% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like rain and rot together, a woma" | | 1 | "looked like captured smoke and another se" |
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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 | 1094 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 53 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 42.08 | | std | 29.84 | | cv | 0.709 | | sampleLengths | | 0 | 100 | | 1 | 13 | | 2 | 51 | | 3 | 72 | | 4 | 17 | | 5 | 48 | | 6 | 9 | | 7 | 66 | | 8 | 41 | | 9 | 6 | | 10 | 104 | | 11 | 62 | | 12 | 31 | | 13 | 5 | | 14 | 53 | | 15 | 31 | | 16 | 12 | | 17 | 8 | | 18 | 36 | | 19 | 28 | | 20 | 113 | | 21 | 42 | | 22 | 41 | | 23 | 55 | | 24 | 13 | | 25 | 37 |
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| 83.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 49 | | matches | | 0 | "was stitched" | | 1 | "been paid" | | 2 | "was gone" |
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| 87.01% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 177 | | matches | | 0 | "was still breathing" | | 1 | "was like shouting" | | 2 | "was looking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 53 | | ratio | 0.132 | | matches | | 0 | "She'd clocked him three weeks back — a courier, mid-twenties, always moving between the Nest and points unknown with a satchel he guarded like it held his own heartbeat." | | 1 | "At the bottom, where the platform should have been dark and empty and smelling of diesel ghosts, there was light instead — a low amber glow, and voices, and the unmistakable murmur of commerce." | | 2 | "Her suspect was thirty feet ahead, shoving through the crowd, and the crowd — God, the crowd." | | 3 | "She realized, with a cold drop in her gut, that shouting *police* here was like shouting *weather* — a fact of the upper world that held no particular authority." | | 4 | "\"You do, actually.\" He smiled, and it was the smile that decided her — the specific, terrible calm of a man who knew the ground had shifted permanently in his favor." | | 5 | "She thought of Morris — the last case, the locked room, the burn marks on the ceiling that no fire investigator could explain, the reports she'd rewritten four times until they said something a coroner would sign." | | 6 | "Somewhere ahead, laughter — human, definitely human, familiar in its cadence if not its owner — drifted from deeper in the market, past a curve where the tunnel dipped from amber light into shadow thick enough to swallow a person whole." |
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| 92.71% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 269 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.048327137546468404 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.01486988847583643 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 53 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 53 | | mean | 20.64 | | std | 14.6 | | cv | 0.707 | | sampleLengths | | 0 | 19 | | 1 | 25 | | 2 | 56 | | 3 | 13 | | 4 | 3 | | 5 | 6 | | 6 | 42 | | 7 | 29 | | 8 | 43 | | 9 | 4 | | 10 | 13 | | 11 | 26 | | 12 | 22 | | 13 | 9 | | 14 | 7 | | 15 | 33 | | 16 | 26 | | 17 | 34 | | 18 | 7 | | 19 | 6 | | 20 | 35 | | 21 | 37 | | 22 | 32 | | 23 | 17 | | 24 | 7 | | 25 | 12 | | 26 | 26 | | 27 | 13 | | 28 | 18 | | 29 | 5 | | 30 | 2 | | 31 | 4 | | 32 | 18 | | 33 | 29 | | 34 | 26 | | 35 | 3 | | 36 | 2 | | 37 | 7 | | 38 | 5 | | 39 | 8 | | 40 | 31 | | 41 | 5 | | 42 | 28 | | 43 | 50 | | 44 | 37 | | 45 | 26 | | 46 | 42 | | 47 | 41 | | 48 | 6 | | 49 | 5 |
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| 56.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.4528301886792453 | | totalSentences | 53 | | uniqueOpeners | 24 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 46 | | matches | | 0 | "Somewhere below, his footsteps slapped" | | 1 | "Somewhere ahead, laughter — human," |
| | ratio | 0.043 | |
| 28.70% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 46 | | matches | | 0 | "She'd been running for six" | | 1 | "She knew exactly how long" | | 2 | "Her voice cracked against the" | | 3 | "He didn't stop." | | 4 | "He never did, the smart" | | 5 | "He cut left down Bayham" | | 6 | "She'd clocked him three weeks" | | 7 | "She didn't like coincidences." | | 8 | "She liked them less when" | | 9 | "He went straight for it," | | 10 | "Her palms scraped raw on" | | 11 | "She dropped down the other" | | 12 | "She saw shelves of bottled" | | 13 | "Her suspect was thirty feet" | | 14 | "She realized, with a cold" | | 15 | "Her suspect reached a stall" | | 16 | "He smiled, and it was" | | 17 | "He turned and was gone," | | 18 | "She thought of Morris —" | | 19 | "She thought about how she'd" |
| | ratio | 0.478 | |
| 57.83% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 37 | | totalSentences | 46 | | matches | | 0 | "Rain came down in sheets" | | 1 | "She'd been running for six" | | 2 | "She knew exactly how long" | | 3 | "Her voice cracked against the" | | 4 | "He didn't stop." | | 5 | "He never did, the smart" | | 6 | "He cut left down Bayham" | | 7 | "She'd clocked him three weeks" | | 8 | "Tonight she'd finally gotten close" | | 9 | "She didn't like coincidences." | | 10 | "She liked them less when" | | 11 | "The alley spat them both" | | 12 | "He went straight for it," | | 13 | "Quinn muttered, and went after" | | 14 | "Her palms scraped raw on" | | 15 | "She dropped down the other" | | 16 | "Quinn stopped so fast her" | | 17 | "The platform had become something" | | 18 | "Stalls ran the length of" | | 19 | "She saw shelves of bottled" |
| | ratio | 0.804 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 46 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 9 | | matches | | 0 | "Rain came down in sheets over Camden, turning the pavement into a black mirror that shattered under Quinn's boots." | | 1 | "She'd been running for six minutes by her count, lungs burning, the leather watch on her wrist ticking uselessly against a stopwatch she didn't need." | | 2 | "Tonight she'd finally gotten close enough to see what was stitched into the leather: a symbol she didn't recognize, silver thread on black, something that made …" | | 3 | "She dropped down the other side into a stairwell that smelled of ozone and mildew, steps slick with algae, no light except the phone she pulled and thumbed into…" | | 4 | "Stalls ran the length of the old track, built from packing crates and drapes of oilcloth, lit by candles in jars and by lanterns that burned with a flame too bl…" | | 5 | "She saw shelves of bottled things that moved on their own, bundles of herbs that smelled like rain and rot together, a woman with silver eyes weighing something…" | | 6 | "She realized, with a cold drop in her gut, that shouting *police* here was like shouting *weather* — a fact of the upper world that held no particular authority…" | | 7 | "He turned and was gone, swallowed between a stall selling jars of something that looked like captured smoke and another selling knives that hummed faintly on th…" | | 8 | "Quinn stood at the edge of the platform, rain still dripping off her coat onto stone that had never known rain, and felt eighteen years of procedure screaming a…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 25.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Quinn muttered (mutter)" |
| | dialogueSentences | 8 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.5 | | effectiveRatio | 0.25 | |