Run: 2026-07-01-01KWEA5AWGCR0CVDPMRBJYR44S

Run Details

Duration:
34.8s
Cost:
$0.023850
Provider:
Amazon Bedrock

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<codex> <character id="4416" name="Detective Harlow Quinn" aliases="Quinn, Detective Quinn, Harlow" pronouns="she/her" species="Human" storyRole="Antagonist"> <eyeColor>brown</eyeColor> <hair>closely cropped salt-and-pepper</hair> <height>5'9"</height> <age>41</age> <jawline>sharp jaw</jawline> <watch>worn leather watch on her left wrist</watch> <bearing>military precision</bearing> <description>A Metropolitan Police detective with 18 years of decorated service who suspects the clique is involved in criminal activity.</description> <backstory>She lost her partner, DS Morris, during a case three years ago under unexplained circumstances that had supernatural origins she doesn't yet understand.</backstory> </character> <character id="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend"> <eyeColor>green</eyeColor> <hair>curly red</hair> <height>5'4"</height> <age>26</age> <glasses>round glasses</glasses> <satchel>worn leather satchel full of books</satchel> <freckles>freckled complexion</freckles> <nervousHabit>tucking hair behind her left ear</nervousHabit> <description>Aurora's childhood friend and an occult researcher.</description> <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory> </character> <location id="856" name="The Veil Market" aliases="Veil Market, the Market, underground market" realm="Earth"> <currentLocation>abandoned Tube station beneath Camden</currentLocation> <entryRequirement>bone token</entryRequirement> <schedule>moves locations every full moon</schedule> <description>A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information.</description> </location> <item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market"> <casingMaterial>small brass compass</casingMaterial> <faceMarkings>face etched with protective sigils</faceMarkings> <needle>points toward the nearest supernatural rift or portal</needle> <patina>casing has a patina of verdigris</patina> <creator>crafted by a Shade artisan</creator> <description>A compass attuned to supernatural energy.</description> </item> </codex> Write a fully fleshed out scene of at least 1000 words in the mystery genre. A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed. Use the codex entries above as your world reference for characters and setting. Only include the prose of the scene without any markdown or commentary.

Model response

AI
The Camden platform smelled of ozone and rust, a combination Detective Harlow Quinn had never once encountered in eighteen years of London policing, and she'd encountered most things London had to offer. She ducked under the tape strung across the boarded entrance—condemned since '89, according to the peeling Transport for London notice bolted to the grate—and let her torch beam slide along the tiled wall. BELSIZE PARK, the tiles read in faded municipal serif, though every map she'd consulted on the drive over insisted this station didn't exist. Not officially. Not anymore. "Whoever called it in didn't leave a name," said DC Ravi Patel, crouching beside the body with the particular stillness of a man trying not to look too closely at something. "Anonymous tip to the non-emergency line. Bloke said he heard screaming from the old station grate on Buck Street." "And uniform just let themselves in." "Grate was already open, ma'am." Quinn crossed the platform, her boots crunching on decades of grit and pigeon droppings, and knelt across from Patel. The dead man lay on his back between two rusted support struts, arms flung wide, mouth open in an expression she'd seen perhaps a dozen times in her career—the specific rictus of a person who had died mid-scream and never gotten to finish it. "ID?" "Nothing on him. No wallet, no phone, no keys. Pockets turned out—but not by us." "Turned out by whom, then?" Patel didn't answer that. He had a habit, lately, of not answering her when the answer made him uncomfortable. Three years they'd worked together on and off, ever since Morris—ever since the thing with Morris that nobody in the department wanted to properly discuss—and Quinn had learned to read the silences as clearly as the words. She examined the body without touching it. Male, mid-thirties, dressed in a good wool coat that had cost more than her monthly rent. No visible wounds. No blood, which struck her first, because a man didn't die like that—face locked in terror, fingers clawed into the platform grit hard enough to break three nails—without something *causing* it, and causing usually meant bleeding. "Cardiac event," Patel offered. "That's my read. Fright, maybe. Wrong place, wrong time, heart just—stopped." "On an abandoned Tube platform. At two in the morning. Wearing a coat that costs eight hundred pounds and no wallet to his name." "People go strange places to do strange things, ma'am." "People don't crawl through a locked grate to have a heart attack, Patel." She leaned closer, careful not to disturb anything, and studied the tiles beneath the body. There—faint, but there, a discoloration in the grout between tiles, a pattern radiating outward from where the man's head lay like the whorl of a fingerprint. She'd seen that pattern before. Once. Three years ago, on a warehouse floor in Deptford, the night she'd lost Morris and half the department had quietly agreed never to speak of the details in the official report. "There's scoring on the wall," she said, standing. "Six feet up. Looks fresh." Patel followed her gaze reluctantly. Four parallel gouges raked into the old tile, too high for a man to have made falling, too deep for anything with fingernails she'd ever catalogued. "Vandalism," he said. "Kids get down here sometimes. Bored, looking for a thrill, bring crowbars—" "Crowbars don't curve, Detective Constable." She traced the air an inch from the marks without touching them. "These curve. Like something raked downward and inward. Like a hand three sizes too large closing around something it meant to catch." "With respect, ma'am, that's a bit of a leap—" "Is it." She turned back to the body, crouched again, and this time she did what she'd been putting off: she loosened the dead man's collar and looked at his throat. No bruising. No ligature marks. But the skin there had a faint blue tracery beneath it, like frost patterns on a windowpane, branching up from his collarbone toward his jaw. She'd seen that too. In her nightmares, mostly, in the three years since. Morris's hands had looked like that, in the last photograph anyone ever took of him, before the department quietly closed the file and quietly requested she take some leave and quietly stopped inviting her to certain briefings. "Ma'am?" Patel's voice had gone careful. "You've gone a bit pale." "I'm fine." She wasn't. She made herself breathe, made herself think like the detective she still was rather than the woman who'd spent three years chasing shadows nobody else believed existed. "Get SOCO down here. Full workup, and I want photographs of that scoring before anyone decides it's not relevant. And Patel—find out who owns that coat. Someone spent good money dressing this man before something down here undressed his soul." "That's a strange way to put it." "It's a strange scene." She straightened, pressing her palm briefly to the small of her back where the old ache lived, and looked once more at the frost-blue tracery vanishing beneath the dead man's collar. Somewhere in this city there were people who understood what made marks like that—people she'd been circling for months now, a loose knit group who moved through London's stranger corners with a confidence that told her they knew exactly what lurked in condemned Tube stations at two in the morning. She didn't have names yet. She had a redheaded researcher spotted twice near restricted collections at the British Museum, and a young woman with her whom witnesses kept describing in contradictory, half-remembered terms, as though memory itself slid away from her. She had patience, too. Eighteen years of it. "Ma'am." Patel had straightened, was watching her with the particular wariness he'd worn since Deptford, since he'd started to suspect his superior officer was chasing something the rest of the department had filed under closed. "What do you think happened here?" Quinn looked at the gouges in the tile, six feet up, curved like grasping fingers, and did not say what she was thinking—that eighteen years of decorated service had taught her to trust evidence over explanation, and the evidence here refused, point-blank, to be ordinary. "I think," she said instead, "we've found our way into something considerably larger than a body on a platform. Get the tent up. And Patel—when SOCO photograph that wall, make sure they get the scale marker in frame. I want to know exactly how large a hand made those marks."
created_at"2026-07-01T07:44:10.652Z" 7/1/2026, 7:44:10 AM
model"anthropic/claude-sonnet-5-20260630"
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external_user(null)
streamedtrue
cancelledfalse
latency1567
moderation_latency(null)
generation_time34751
tokens_prompt923
tokens_completion1673
native_tokens_prompt1285
native_tokens_completion2128
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"end_turn"
service_tier"default"
usage0.02385
router(null)
provider_responses
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endpoint_id"37b16f45-eeae-45f3-9b85-2137f7c6d61b"
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is_byokfalse
latency1567
model_permaslug"anthropic/claude-sonnet-5-20260630"
provider_name"Amazon Bedrock"
status200
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request_id"req-1782891850-0RnDl9V7Zhbrh5j9Le7J"
session_id(null)
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api_type"completions"
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total_cost0.02385
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provider_name"Amazon Bedrock"
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data_region"global"

Evaluation details

Result Evaluator Details Meta Data
62.07% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags12
adverbTagCount2
adverbTags
0"She turned back [back]"
1"she said instead [instead]"
dialogueSentences29
tagDensity0.414
leniency0.828
rawRatio0.167
effectiveRatio0.138
95.39% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1084
totalAiIsmAdverbs1
found
0
adverb"reluctantly"
count1
highlights
0"reluctantly"
80.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found
0"Patel"
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
95.39% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1084
totalAiIsms1
found
0
word"traced"
count1
highlights
0"traced"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches0
maxInWindow0
found(empty)
highlights(empty)
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells1
narrationSentences45
matches
0"d in terror"
79.37% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences45
filterMatches
0"think"
hedgeMatches
0"started to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences62
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen51
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords1
totalWords1071
ratio0.001
matches
0"causing"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions12
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions27
wordCount757
uniqueNames12
maxNameDensity0.92
worstName"Patel"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Camden1
Detective1
Harlow1
Quinn4
London3
Ravi1
Patel7
Morris4
Deptford2
Tube1
British1
Museum1
persons
0"Harlow"
1"Quinn"
2"Ravi"
3"Patel"
4"Morris"
places
0"London"
1"Deptford"
2"British"
globalScore1
windowScore1
53.85% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences26
glossingSentenceCount1
matches
0"looked like that, in the last photograph"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1071
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences62
matches
0"seen that pattern"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs30
mean35.7
std29.54
cv0.827
sampleLengths
065
127
250
36
45
563
61
715
85
956
1062
1115
1224
139
1491
1513
1631
1715
1839
199
2061
2150
2211
2371
247
25126
268
2741
2845
2950
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences45
matches(empty)
47.33% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs131
matches
0"was watching"
1"was chasing"
2"was thinking"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount9
semicolonCount0
flaggedSentences7
totalSentences62
ratio0.113
matches
0"She ducked under the tape strung across the boarded entrance—condemned since '89, according to the peeling Transport for London notice bolted to the grate—and let her torch beam slide along the tiled wall."
1"The dead man lay on his back between two rusted support struts, arms flung wide, mouth open in an expression she'd seen perhaps a dozen times in her career—the specific rictus of a person who had died mid-scream and never gotten to finish it."
2"Three years they'd worked together on and off, ever since Morris—ever since the thing with Morris that nobody in the department wanted to properly discuss—and Quinn had learned to read the silences as clearly as the words."
3"No blood, which struck her first, because a man didn't die like that—face locked in terror, fingers clawed into the platform grit hard enough to break three nails—without something *causing* it, and causing usually meant bleeding."
4"There—faint, but there, a discoloration in the grout between tiles, a pattern radiating outward from where the man's head lay like the whorl of a fingerprint."
5"Somewhere in this city there were people who understood what made marks like that—people she'd been circling for months now, a loose knit group who moved through London's stranger corners with a confidence that told her they knew exactly what lurked in condemned Tube stations at two in the morning."
6"Quinn looked at the gouges in the tile, six feet up, curved like grasping fingers, and did not say what she was thinking—that eighteen years of decorated service had taught her to trust evidence over explanation, and the evidence here refused, point-blank, to be ordinary."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount284
adjectiveStacks0
stackExamples(empty)
adverbCount11
adverbRatio0.03873239436619718
lyAdverbCount2
lyAdverbRatio0.007042253521126761
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences62
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences62
mean17.27
std14.32
cv0.829
sampleLengths
032
133
223
32
42
531
619
76
85
919
1044
111
1215
135
144
1515
1637
177
1816
193
2036
214
2211
2324
249
2528
2626
275
281
2931
308
315
325
3326
343
3512
3617
3722
389
3931
402
413
4225
434
449
4537
466
475
484
4927
90.32% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats6
diversityRatio0.6774193548387096
totalSentences62
uniqueOpeners42
87.72% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences38
matches
0"Somewhere in this city there"
ratio0.026
62.11% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount15
totalSentences38
matches
0"She ducked under the tape"
1"He had a habit, lately,"
2"She examined the body without"
3"She leaned closer, careful not"
4"She'd seen that pattern before."
5"she said, standing"
6"She traced the air an"
7"She turned back to the"
8"She'd seen that too."
9"She made herself breathe, made"
10"She straightened, pressing her palm"
11"She didn't have names yet."
12"She had a redheaded researcher"
13"She had patience, too."
14"she said instead"
ratio0.395
100.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount25
totalSentences38
matches
0"The Camden platform smelled of"
1"She ducked under the tape"
2"Quinn crossed the platform, her"
3"The dead man lay on"
4"Patel didn't answer that."
5"He had a habit, lately,"
6"She examined the body without"
7"She leaned closer, careful not"
8"There—faint, but there, a discoloration"
9"She'd seen that pattern before."
10"she said, standing"
11"Patel followed her gaze reluctantly."
12"She traced the air an"
13"She turned back to the"
14"She'd seen that too."
15"Morris's hands had looked like"
16"Patel's voice had gone careful"
17"She made herself breathe, made"
18"She straightened, pressing her palm"
19"She didn't have names yet."
ratio0.658
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences38
matches(empty)
ratio0
0.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences17
technicalSentenceCount5
matches
0"The dead man lay on his back between two rusted support struts, arms flung wide, mouth open in an expression she'd seen perhaps a dozen times in her career—the …"
1"Male, mid-thirties, dressed in a good wool coat that had cost more than her monthly rent."
2"No blood, which struck her first, because a man didn't die like that—face locked in terror, fingers clawed into the platform grit hard enough to break three nai…"
3"Somewhere in this city there were people who understood what made marks like that—people she'd been circling for months now, a loose knit group who moved throug…"
4"She had a redheaded researcher spotted twice near restricted collections at the British Museum, and a young woman with her whom witnesses kept describing in con…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags12
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount0
fancyTags(empty)
dialogueSentences29
tagDensity0.138
leniency0.276
rawRatio0
effectiveRatio0
81.7843%